ferrox_quant/

repack.rs

//! Interleaved Q4_K / Q5_K × Q8_K and Q8_0 × Q8 GEMV (llama.cpp repack layouts).
//!
//! - Q4_K: packs 8 rows into `block_q4_Kx8` (`make_block_q4_Kx8`).
//! - Q5_K: packs 8 rows into `block_q5_Kx8` (`make_block_q5_Kx8`).
//! - Q8_0: packs 4 rows into `block_q8_0x4` (`make_block_q8_0x4`) with
//!   4-byte interleave for NEON SDOT `ggml_gemv_q8_0_4x4_q8_0`.
//! - Q4_0: packs 4 rows into `block_q4_0x4` (`make_block_q4_0x4`) with
//!   4-byte interleave + XOR `0x88888888` for `ggml_gemv_q4_0_4x4_q8_0`.
//!
//! Gated on `FERROX_CPU_INT_DOT`, which `ferrox` and `ferrox-server`
//! turn on by default (`=0` opts out); off in the library so golden
//! cross-validation stays reference-exact.

use crate::{
    Q8Activations, Q8KActivations, Q4_0_BLOCK_BYTES, Q4_0_BLOCK_ELEMS, Q4_K_BLOCK_BYTES,
    Q4_K_BLOCK_ELEMS, Q5_K_BLOCK_BYTES, Q5_K_BLOCK_ELEMS, Q6_K_BLOCK_BYTES, Q6_K_BLOCK_ELEMS,
    Q8_0_BLOCK_BYTES, Q8_0_BLOCK_ELEMS,
};
use half::f16;

/// Bytes per interleaved `block_q4_Kx8` (8 × f16 d + 8 × f16 dmin + 96 scales + 1024 qs).
pub const Q4_KX8_BLOCK_BYTES: usize = 1152;
/// Number of Q4_K rows packed into one interleaved block.
pub const Q4_KX8_NROWS: usize = 8;

const KMASK1: u32 = 0x3f3f_3f3f;
const KMASK2: u32 = 0x0f0f_0f0f;
const KMASK3: u32 = 0x0303_0303;

/// Preferred qs interleave width for this CPU: 8 on x86 AVX2 and ARM i8mm
/// (`ggml_gemm_q4_K_8x8_q8_K`), 4 on DotProd-only NEON (`ggml_gemm_q4_K_8x4_q8_K`).
#[inline]
pub fn q4_kx8_interleave() -> usize {
    if cfg!(target_arch = "x86_64") {
        return 8;
    }
    #[cfg(target_arch = "aarch64")]
    {
        if std::arch::is_aarch64_feature_detected!("i8mm") {
            return 8;
        }
    }
    4
}

#[inline]
fn f16_from_bytes(b: &[u8]) -> f32 {
    f16::from_le_bytes([b[0], b[1]]).to_f32()
}

/// Pack eight canonical Q4_K super-blocks (same column-block index) into
/// one `block_q4_Kx8`. `interleave` is 4 (ARM DotProd) or 8 (x86 / ARM i8mm).
pub fn make_block_q4_kx8(
    rows: [&[u8]; Q4_KX8_NROWS],
    interleave: usize,
) -> [u8; Q4_KX8_BLOCK_BYTES] {
    debug_assert!(interleave == 4 || interleave == 8);
    for r in &rows {
        debug_assert_eq!(r.len(), Q4_K_BLOCK_BYTES);
    }
    let mut out = [0u8; Q4_KX8_BLOCK_BYTES];
    // d[8] at 0, dmin[8] at 16, scales[96] at 32, qs[1024] at 128.
    for (i, row) in rows.iter().enumerate() {
        out[i * 2] = row[0];
        out[i * 2 + 1] = row[1];
        out[16 + i * 2] = row[2];
        out[16 + i * 2 + 1] = row[3];
    }

    let end = (Q4_K_BLOCK_ELEMS * 4) / interleave; // qs bytes * 8 rows / interleave
    let qs_out = &mut out[128..];
    for i in 0..end {
        let src_id = i % Q4_KX8_NROWS;
        let src_offset = (i / Q4_KX8_NROWS) * interleave;
        let dst_offset = i * interleave;
        let src_qs = &rows[src_id][16..144];
        qs_out[dst_offset..dst_offset + interleave]
            .copy_from_slice(&src_qs[src_offset..src_offset + interleave]);
    }

    // Rearrange 6-bit scales/mins across 8 rows into 96 packed bytes
    // (llama.cpp `make_block_q4_Kx8`).
    let mut s = [0u8; 8];
    let mut m = [0u8; 8];
    let scales_out = &mut out[32..128];

    for i in 0..4 {
        for j in 0..8 {
            let sc = &rows[j][4..16];
            s[j] = sc[i] & 63;
            m[j] = sc[i + 4] & 63;
        }
        let base = i * 12;
        scales_out[base] = (s[0] & 63) + ((s[4] & 48) << 2);
        scales_out[base + 1] = (s[1] & 63) + ((s[5] & 48) << 2);
        scales_out[base + 2] = (s[2] & 63) + ((s[6] & 48) << 2);
        scales_out[base + 3] = (s[3] & 63) + ((s[7] & 48) << 2);
        scales_out[base + 4] = (m[0] & 63) + ((m[4] & 48) << 2);
        scales_out[base + 5] = (m[1] & 63) + ((m[5] & 48) << 2);
        scales_out[base + 6] = (m[2] & 63) + ((m[6] & 48) << 2);
        scales_out[base + 7] = (m[3] & 63) + ((m[7] & 48) << 2);
        scales_out[base + 8] = (s[4] & 15) + ((m[4] & 15) << 4);
        scales_out[base + 9] = (s[5] & 15) + ((m[5] & 15) << 4);
        scales_out[base + 10] = (s[6] & 15) + ((m[6] & 15) << 4);
        scales_out[base + 11] = (s[7] & 15) + ((m[7] & 15) << 4);
    }

    for i in 0..4 {
        for j in 0..8 {
            let sc = &rows[j][4..16];
            s[j] = ((sc[i] & 192) >> 2) | (sc[i + 8] & 15);
            m[j] = ((sc[i + 4] & 192) >> 2) | ((sc[i + 8] & 240) >> 4);
        }
        let base = 48 + i * 12;
        scales_out[base] = (s[0] & 63) + ((s[4] & 48) << 2);
        scales_out[base + 1] = (s[1] & 63) + ((s[5] & 48) << 2);
        scales_out[base + 2] = (s[2] & 63) + ((s[6] & 48) << 2);
        scales_out[base + 3] = (s[3] & 63) + ((s[7] & 48) << 2);
        scales_out[base + 4] = (m[0] & 63) + ((m[4] & 48) << 2);
        scales_out[base + 5] = (m[1] & 63) + ((m[5] & 48) << 2);
        scales_out[base + 6] = (m[2] & 63) + ((m[6] & 48) << 2);
        scales_out[base + 7] = (m[3] & 63) + ((m[7] & 48) << 2);
        scales_out[base + 8] = (s[4] & 15) + ((m[4] & 15) << 4);
        scales_out[base + 9] = (s[5] & 15) + ((m[5] & 15) << 4);
        scales_out[base + 10] = (s[6] & 15) + ((m[6] & 15) << 4);
        scales_out[base + 11] = (s[7] & 15) + ((m[7] & 15) << 4);
    }

    out
}

/// Repack a full Q4_K matrix (row-major canonical blocks) into interleaved
/// `block_q4_Kx8` groups. Rows not divisible by 8 are left out (caller
/// handles the tail with per-row dots). `interleave` defaults via
/// [`q4_kx8_interleave`].
pub fn pack_q4_k_matrix_x8(data: &[u8], rows: usize, cols: usize, interleave: usize) -> Vec<u8> {
    assert!(cols.is_multiple_of(Q4_K_BLOCK_ELEMS));
    let n_blocks = cols / Q4_K_BLOCK_ELEMS;
    let row_bytes = n_blocks * Q4_K_BLOCK_BYTES;
    assert_eq!(data.len(), rows * row_bytes);
    let n_groups = rows / Q4_KX8_NROWS;
    let mut out = Vec::with_capacity(n_groups * n_blocks * Q4_KX8_BLOCK_BYTES);
    for g in 0..n_groups {
        for b in 0..n_blocks {
            let mut row_refs: [&[u8]; Q4_KX8_NROWS] = [&[]; Q4_KX8_NROWS];
            for (r, slot) in row_refs.iter_mut().enumerate() {
                let base = (g * Q4_KX8_NROWS + r) * row_bytes + b * Q4_K_BLOCK_BYTES;
                *slot = &data[base..base + Q4_K_BLOCK_BYTES];
            }
            out.extend_from_slice(&make_block_q4_kx8(row_refs, interleave));
        }
    }
    out
}

/// Decode one 12-byte packed scale/min group into 8 scales + 8 mins (u8).
#[inline]
fn decode_scales_mins(scales12: &[u8], scales_out: &mut [u8; 8], mins_out: &mut [u8; 8]) {
    debug_assert!(scales12.len() >= 12);
    let mut utmp = [0u32; 4];
    utmp[0] = u32::from_le_bytes(scales12[0..4].try_into().unwrap());
    utmp[1] = u32::from_le_bytes(scales12[4..8].try_into().unwrap());
    utmp[2] = u32::from_le_bytes(scales12[8..12].try_into().unwrap());
    utmp[3] = ((utmp[2] >> 4) & KMASK2) | (((utmp[1] >> 6) & KMASK3) << 4);
    let uaux_0 = utmp[1] & KMASK1;
    utmp[1] = (utmp[2] & KMASK2) | (((utmp[0] >> 6) & KMASK3) << 4);
    utmp[2] = uaux_0;
    utmp[0] &= KMASK1;
    let bytes = unsafe { std::slice::from_raw_parts(utmp.as_ptr() as *const u8, 16) };
    scales_out.copy_from_slice(&bytes[0..8]);
    mins_out.copy_from_slice(&bytes[8..16]);
}

/// Scalar GEMV for interleave=4 (`ggml_gemv_q4_K_8x4_q8_K_generic`).
fn gemv_q4_kx8_q8_k_scalar_4(
    packed: &[u8],
    act: &Q8KActivations,
    n_cols: usize,
    n_row_groups: usize,
    out: &mut [f32],
) {
    let nb = n_cols / Q4_K_BLOCK_ELEMS;
    let blocklen = 4;
    let ncols_interleaved = Q4_KX8_NROWS;
    debug_assert_eq!(act.n_blocks(), nb);
    debug_assert_eq!(out.len(), n_row_groups * ncols_interleaved);
    debug_assert_eq!(packed.len(), n_row_groups * nb * Q4_KX8_BLOCK_BYTES);

    for x in 0..n_row_groups {
        let mut sumf = [0f32; 8];
        let mut sum_minf = [0f32; 8];
        let group_off = x * nb * Q4_KX8_BLOCK_BYTES;
        for l in 0..nb {
            let blk = &packed[group_off + l * Q4_KX8_BLOCK_BYTES..][..Q4_KX8_BLOCK_BYTES];
            let d = &blk[0..16];
            let dmin = &blk[16..32];
            let scales = &blk[32..128];
            let qs = &blk[128..];
            let da = act.d[l];
            let q8 = &act.q[l * Q4_K_BLOCK_ELEMS..(l + 1) * Q4_K_BLOCK_ELEMS];
            let bsums = &act.bsums[l * 16..(l + 1) * 16];

            let mut all_scales = [[0u8; 8]; 8];
            let mut all_mins = [[0u8; 8]; 8];
            for sb in 0..8 {
                decode_scales_mins(&scales[sb * 12..], &mut all_scales[sb], &mut all_mins[sb]);
            }

            let n_k = Q4_K_BLOCK_ELEMS / (2 * blocklen); // 32
            for k in 0..n_k {
                let sb_pair = k / 8;
                let sc0 = &all_scales[sb_pair * 2];
                let sc1 = &all_scales[sb_pair * 2 + 1];
                for j in 0..ncols_interleaved {
                    let mut sumi = 0i32;
                    for i in 0..blocklen {
                        let qbyte = qs[k * ncols_interleaved * blocklen + j * blocklen + i];
                        let v0 = (qbyte & 0x0F) as i32;
                        let v1 = (qbyte >> 4) as i32;
                        let a0 = q8[(k / 8) * 64 + (k % 8) * blocklen + i] as i32;
                        let a1 = q8[(k / 8) * 64 + (k % 8) * blocklen + i + 32] as i32;
                        sumi += v0 * a0 * sc0[j] as i32 + v1 * a1 * sc1[j] as i32;
                    }
                    sumf[j] += sumi as f32 * f16_from_bytes(&d[j * 2..]) * da;
                }
            }
            for sb in 0..8 {
                let mins = &all_mins[sb];
                let bsum = bsums[sb * 2] as i32 + bsums[sb * 2 + 1] as i32;
                for j in 0..ncols_interleaved {
                    sum_minf[j] +=
                        mins[j] as f32 * bsum as f32 * f16_from_bytes(&dmin[j * 2..]) * da;
                }
            }
        }
        let base = x * ncols_interleaved;
        for j in 0..ncols_interleaved {
            out[base + j] = sumf[j] - sum_minf[j];
        }
    }
}

/// Scalar GEMV for interleave=8 (`ggml_gemv_q4_K_8x8_q8_K_generic`).
fn gemv_q4_kx8_q8_k_scalar_8(
    packed: &[u8],
    act: &Q8KActivations,
    n_cols: usize,
    n_row_groups: usize,
    out: &mut [f32],
) {
    let nb = n_cols / Q4_K_BLOCK_ELEMS;
    let blocklen = 8;
    let ncols_interleaved = Q4_KX8_NROWS;
    debug_assert_eq!(act.n_blocks(), nb);
    debug_assert_eq!(out.len(), n_row_groups * ncols_interleaved);

    for x in 0..n_row_groups {
        let mut sumf = [0f32; 8];
        let mut sum_minf = [0f32; 8];
        let group_off = x * nb * Q4_KX8_BLOCK_BYTES;
        for l in 0..nb {
            let blk = &packed[group_off + l * Q4_KX8_BLOCK_BYTES..][..Q4_KX8_BLOCK_BYTES];
            let d = &blk[0..16];
            let dmin = &blk[16..32];
            let scales = &blk[32..128];
            let qs = &blk[128..];
            let da = act.d[l];
            let q8 = &act.q[l * Q4_K_BLOCK_ELEMS..(l + 1) * Q4_K_BLOCK_ELEMS];
            let bsums = &act.bsums[l * 16..(l + 1) * 16];

            let mut all_scales = [[0u8; 8]; 8];
            let mut all_mins = [[0u8; 8]; 8];
            for sb in 0..8 {
                decode_scales_mins(&scales[sb * 12..], &mut all_scales[sb], &mut all_mins[sb]);
            }

            let n_k = Q4_K_BLOCK_ELEMS / (2 * blocklen); // 16
            for k in 0..n_k {
                let sb_pair = k / 4;
                let sc0 = &all_scales[sb_pair * 2];
                let sc1 = &all_scales[sb_pair * 2 + 1];
                for j in 0..ncols_interleaved {
                    let mut sumi = 0i32;
                    for i in 0..blocklen {
                        let qbyte = qs[k * ncols_interleaved * blocklen + j * blocklen + i];
                        let v0 = (qbyte & 0x0F) as i32;
                        let v1 = (qbyte >> 4) as i32;
                        let a0 = q8[(k >> 2) * 64 + (k % 4) * blocklen + i] as i32;
                        let a1 = q8[(k >> 2) * 64 + (k % 4) * blocklen + i + 32] as i32;
                        sumi += v0 * a0 * sc0[j] as i32 + v1 * a1 * sc1[j] as i32;
                    }
                    sumf[j] += sumi as f32 * f16_from_bytes(&d[j * 2..]) * da;
                }
            }
            for sb in 0..8 {
                let mins = &all_mins[sb];
                let bsum = bsums[sb * 2] as i32 + bsums[sb * 2 + 1] as i32;
                for j in 0..ncols_interleaved {
                    sum_minf[j] +=
                        mins[j] as f32 * bsum as f32 * f16_from_bytes(&dmin[j * 2..]) * da;
                }
            }
        }
        let base = x * ncols_interleaved;
        for j in 0..ncols_interleaved {
            out[base + j] = sumf[j] - sum_minf[j];
        }
    }
}

/// GEMV: interleaved Q4_K weights × Q8_K activation → `n_row_groups * 8` f32s.
/// Dispatches to NEON (both interleaves) / AVX2 (interleave 8) when available.
pub fn gemv_q4_kx8_q8_k(
    packed: &[u8],
    act: &Q8KActivations,
    n_cols: usize,
    n_row_groups: usize,
    interleave: usize,
    out: &mut [f32],
) {
    assert!(n_cols.is_multiple_of(Q4_K_BLOCK_ELEMS));
    assert_eq!(out.len(), n_row_groups * Q4_KX8_NROWS);
    match interleave {
        4 => {
            #[cfg(target_arch = "aarch64")]
            {
                if std::arch::is_aarch64_feature_detected!("dotprod") {
                    unsafe {
                        neon::gemv_q4_kx8_q8_k_neon_sdot(packed, act, n_cols, n_row_groups, out);
                    }
                    return;
                }
            }
            gemv_q4_kx8_q8_k_scalar_4(packed, act, n_cols, n_row_groups, out);
        }
        8 => {
            #[cfg(target_arch = "x86_64")]
            {
                if is_x86_feature_detected!("avx2") && is_x86_feature_detected!("fma") {
                    unsafe {
                        avx2::gemv_q4_kx8_q8_k_avx2(packed, act, n_cols, n_row_groups, out);
                    }
                    return;
                }
            }
            #[cfg(target_arch = "aarch64")]
            {
                if std::arch::is_aarch64_feature_detected!("dotprod") {
                    unsafe {
                        neon::gemv_q4_kx8_q8_k_neon_8x8(packed, act, n_cols, n_row_groups, out);
                    }
                    return;
                }
            }
            gemv_q4_kx8_q8_k_scalar_8(packed, act, n_cols, n_row_groups, out);
        }
        _ => panic!("q4_kx8 interleave must be 4 or 8, got {interleave}"),
    }
}

/// One row-group (8 outputs) starting at `group` within a packed matrix.
#[inline]
pub fn gemv_q4_kx8_group(
    packed: &[u8],
    group: usize,
    act: &Q8KActivations,
    n_cols: usize,
    interleave: usize,
    out8: &mut [f32],
) {
    debug_assert_eq!(out8.len(), Q4_KX8_NROWS);
    let nb = n_cols / Q4_K_BLOCK_ELEMS;
    let off = group * nb * Q4_KX8_BLOCK_BYTES;
    let slice = &packed[off..off + nb * Q4_KX8_BLOCK_BYTES];
    gemv_q4_kx8_q8_k(slice, act, n_cols, 1, interleave, out8);
}

// ---------------------------------------------------------------------------
// Q8_0 ×4 interleaved GEMV (llama.cpp `block_q8_0x4` / `ggml_gemv_q8_0_4x4`)
// ---------------------------------------------------------------------------

/// Bytes per interleaved `block_q8_0x4` (4 × f16 d + 128 qs).
pub const Q8_0X4_BLOCK_BYTES: usize = 136;
/// Number of Q8_0 rows packed into one interleaved block.
pub const Q8_0X4_NROWS: usize = 4;
/// qs interleave width for `ggml_gemv_q8_0_4x4_q8_0` (NEON SDOT). The
/// DotProd-only default; [`q8_0x4_interleave`] picks 8 on i8mm hosts.
pub const Q8_0X4_INTERLEAVE: usize = 4;

/// Preferred qs interleave width: 8 on ARM i8mm (`ggml_gemm_q8_0_4x8_q8_0`
/// via `ggml_repack_get_optimal_repack_type`), 4 on DotProd-only NEON and
/// everywhere else (the scalar fallback handles either).
#[inline]
pub fn q8_0x4_interleave() -> usize {
    #[cfg(target_arch = "aarch64")]
    {
        if std::arch::is_aarch64_feature_detected!("i8mm") {
            return 8;
        }
    }
    Q8_0X4_INTERLEAVE
}

/// Pack four canonical Q8_0 blocks (same column-block) into one
/// `block_q8_0x4`. `interleave` is 4 (ARM 4x4) or 8 (4x8).
pub fn make_block_q8_0x4(
    rows: [&[u8]; Q8_0X4_NROWS],
    interleave: usize,
) -> [u8; Q8_0X4_BLOCK_BYTES] {
    debug_assert!(interleave == 4 || interleave == 8);
    for r in &rows {
        debug_assert_eq!(r.len(), Q8_0_BLOCK_BYTES);
    }
    let mut out = [0u8; Q8_0X4_BLOCK_BYTES];
    for (i, row) in rows.iter().enumerate() {
        out[i * 2] = row[0];
        out[i * 2 + 1] = row[1];
    }
    let end = (Q8_0_BLOCK_ELEMS * Q8_0X4_NROWS) / interleave;
    let qs_out = &mut out[8..];
    for i in 0..end {
        let src_id = i % Q8_0X4_NROWS;
        let src_offset = (i / Q8_0X4_NROWS) * interleave;
        let dst_offset = i * interleave;
        let src_qs = &rows[src_id][2..34];
        qs_out[dst_offset..dst_offset + interleave]
            .copy_from_slice(&src_qs[src_offset..src_offset + interleave]);
    }
    out
}

/// Repack a Q8_0 matrix into interleaved `block_q8_0x4` groups. Tail rows
/// (not divisible by 4) are omitted; caller dots them with [`crate::dot_q8_0_q8`].
pub fn pack_q8_0_matrix_x4(data: &[u8], rows: usize, cols: usize, interleave: usize) -> Vec<u8> {
    assert!(cols.is_multiple_of(Q8_0_BLOCK_ELEMS));
    let n_blocks = cols / Q8_0_BLOCK_ELEMS;
    let row_bytes = n_blocks * Q8_0_BLOCK_BYTES;
    assert_eq!(data.len(), rows * row_bytes);
    let n_groups = rows / Q8_0X4_NROWS;
    let mut out = Vec::with_capacity(n_groups * n_blocks * Q8_0X4_BLOCK_BYTES);
    for g in 0..n_groups {
        for b in 0..n_blocks {
            let mut row_refs: [&[u8]; Q8_0X4_NROWS] = [&[]; Q8_0X4_NROWS];
            for (r, slot) in row_refs.iter_mut().enumerate() {
                let base = (g * Q8_0X4_NROWS + r) * row_bytes + b * Q8_0_BLOCK_BYTES;
                *slot = &data[base..base + Q8_0_BLOCK_BYTES];
            }
            out.extend_from_slice(&make_block_q8_0x4(row_refs, interleave));
        }
    }
    out
}

/// Scalar GEMV (`ggml_gemv_q8_0_4x{4,8}_q8_0_generic`); `blocklen` is the
/// interleave the matrix was packed with.
fn gemv_q8_0x4_q8_0_scalar(
    packed: &[u8],
    act: &Q8Activations,
    n_cols: usize,
    n_row_groups: usize,
    blocklen: usize,
    out: &mut [f32],
) {
    let nb = n_cols / Q8_0_BLOCK_ELEMS;
    let ncols = Q8_0X4_NROWS;
    debug_assert_eq!(act.n_blocks(), nb);
    debug_assert_eq!(out.len(), n_row_groups * ncols);
    debug_assert_eq!(packed.len(), n_row_groups * nb * Q8_0X4_BLOCK_BYTES);

    for x in 0..n_row_groups {
        let mut sumf = [0f32; 4];
        let group_off = x * nb * Q8_0X4_BLOCK_BYTES;
        for l in 0..nb {
            let blk = &packed[group_off + l * Q8_0X4_BLOCK_BYTES..][..Q8_0X4_BLOCK_BYTES];
            let qs = &blk[8..];
            let da = act.d[l];
            let q8 = &act.q[l * Q8_0_BLOCK_ELEMS..(l + 1) * Q8_0_BLOCK_ELEMS];
            for k in 0..(Q8_0_BLOCK_ELEMS / blocklen) {
                for j in 0..ncols {
                    let mut sumi = 0i32;
                    for i in 0..blocklen {
                        let v0 = qs[k * ncols * blocklen + j * blocklen + i] as i8 as i32;
                        sumi += v0 * q8[k * blocklen + i] as i32;
                    }
                    sumf[j] += sumi as f32 * f16_from_bytes(&blk[j * 2..]) * da;
                }
            }
        }
        let base = x * ncols;
        out[base..base + ncols].copy_from_slice(&sumf);
    }
}

/// GEMV: interleaved Q8_0 weights × Q8 activation → `n_row_groups * 4` f32s.
/// `interleave` must match the packing (4: NEON SDOT `4x4`; 8: NEON `4x8`).
pub fn gemv_q8_0x4_q8_0(
    packed: &[u8],
    act: &Q8Activations,
    n_cols: usize,
    n_row_groups: usize,
    interleave: usize,
    out: &mut [f32],
) {
    assert!(n_cols.is_multiple_of(Q8_0_BLOCK_ELEMS));
    assert_eq!(out.len(), n_row_groups * Q8_0X4_NROWS);
    match interleave {
        4 => {
            #[cfg(target_arch = "aarch64")]
            {
                if std::arch::is_aarch64_feature_detected!("dotprod") {
                    unsafe {
                        neon::gemv_q8_0x4_q8_0_neon_sdot(packed, act, n_cols, n_row_groups, out);
                    }
                    return;
                }
            }
            gemv_q8_0x4_q8_0_scalar(packed, act, n_cols, n_row_groups, 4, out);
        }
        8 => {
            #[cfg(target_arch = "aarch64")]
            {
                if std::arch::is_aarch64_feature_detected!("dotprod") {
                    unsafe {
                        neon::gemv_q8_0x4_q8_0_neon_4x8(packed, act, n_cols, n_row_groups, out);
                    }
                    return;
                }
            }
            gemv_q8_0x4_q8_0_scalar(packed, act, n_cols, n_row_groups, 8, out);
        }
        _ => panic!("q8_0x4 interleave must be 4 or 8, got {interleave}"),
    }
}

/// How many activations one [`gemm_q8_0x4_group`] pass keeps in flight.
/// Four f32x4 accumulators plus the eight loaded weight vectors fit
/// comfortably in NEON's register file, so each weight load is amortized
/// over four activations instead of being repeated per activation.
pub const Q8_0X4_GEMM_NC: usize = 8;

/// GEMM counterpart of [`gemv_q8_0x4_group`]: one row-group (4 rows)
/// against `acts.len()` activations at once.
///
/// The difference that matters is register blocking over the *batch*
/// dimension. Calling the GEMV once per activation reloads the group's
/// eight `int8x16` weight vectors for every activation; this loads them
/// once per `Q8_0X4_GEMM_NC` activations and issues the dot products
/// back to back. That is the same reason llama.cpp ships
/// `ggml_gemm_q8_0_4x4_q8_0` next to `ggml_gemv_q8_0_4x4_q8_0` rather
/// than looping the GEMV.
///
/// `out` is `[row][act]`: `out[r * acts.len() + j]`, which is the layout
/// `WeightMatrix::apply_batch` accumulates into.
pub fn gemm_q8_0x4_group(
    packed: &[u8],
    group: usize,
    acts: &[Q8Activations],
    n_cols: usize,
    interleave: usize,
    out: &mut [f32],
) {
    assert_eq!(out.len(), Q8_0X4_NROWS * acts.len());
    assert!(n_cols.is_multiple_of(Q8_0_BLOCK_ELEMS));
    if acts.is_empty() {
        return;
    }
    let nb = n_cols / Q8_0_BLOCK_ELEMS;
    let off = group * nb * Q8_0X4_BLOCK_BYTES;
    let slice = &packed[off..off + nb * Q8_0X4_BLOCK_BYTES];

    #[cfg(target_arch = "aarch64")]
    {
        if interleave == 8 && std::arch::is_aarch64_feature_detected!("i8mm") {
            // Compatibility entry: interleaves the quads here, once per
            // call. Batch callers should prepare them once per matmul and
            // use [`gemm_q8_0x4_group_x4`] instead.
            for (t, chunk) in acts.chunks(Q8K_ACTS_X4_NC).enumerate() {
                let tile = prepare_q8_acts_x4(chunk, n_cols);
                let mut tmp = [0f32; Q8_0X4_NROWS * Q8K_ACTS_X4_NC];
                let n = chunk.len();
                unsafe {
                    neon::gemm_q8_0x4_q8_0_neon_i8mm(
                        slice,
                        &tile,
                        n_cols,
                        &mut tmp[..Q8_0X4_NROWS * n],
                    );
                }
                for r in 0..Q8_0X4_NROWS {
                    for j in 0..n {
                        out[r * acts.len() + t * Q8K_ACTS_X4_NC + j] = tmp[r * n + j];
                    }
                }
            }
            return;
        }
        if interleave == 4 && std::arch::is_aarch64_feature_detected!("dotprod") {
            unsafe {
                neon::gemm_q8_0x4_q8_0_neon_sdot(slice, acts, n_cols, out);
            }
            return;
        }
    }
    // Portable fallback: the GEMV, once per activation. Same results,
    // none of the reuse.
    let mut tmp = [0f32; Q8_0X4_NROWS];
    for (j, act) in acts.iter().enumerate() {
        gemv_q8_0x4_q8_0(slice, act, n_cols, 1, interleave, &mut tmp);
        for (r, v) in tmp.iter().enumerate() {
            out[r * acts.len() + j] = *v;
        }
    }
}

/// A quad of up to [`Q8K_ACTS_X4_NC`] Q8_0 activations, pre-interleaved
/// into the layout llama.cpp's `ggml_quantize_mat_q8_0_4x8` writes into
/// `block_q8_0x4` (`arch/arm/repack.cpp`): every 32-element block's qs in
/// 8-byte runs, plus the per-block per-row scales. Consumed by the i8mm
/// `4x8` GEMMs; prepared once per matmul, same hoist as [`Q8KActsX4`].
pub struct Q8ActsX4 {
    /// Real activations in the quad (≤ 4); rows `na..4` are zero padding.
    pub na: usize,
    /// Q8_0 blocks per activation (`n_cols / 32`).
    pub n_blocks: usize,
    /// Interleaved quants, `n_blocks * 128` long. Block `b`, 8-element run
    /// `c`, quad row `a`, lane `k` ↦
    /// `qs[b*128 + c*32 + a*8 + k] = acts[a].q[b*32 + c*8 + k]`.
    pub qs: Vec<i8>,
    /// Activation scales, `n_blocks * 4` long: `d[b*4 + a] = acts[a].d[b]`.
    pub d: Vec<f32>,
}

/// Interleave a quad of Q8_0 activations for the `4x8` i8mm GEMMs
/// (llama.cpp `ggml_quantize_mat_q8_0_4x8`, minus the quantization we
/// already did). Zero-pads when `acts.len() < 4`. Available on every
/// target so the portable GEMMs — and the tests pinning the NEON kernels
/// to them — run anywhere.
pub fn prepare_q8_acts_x4(acts: &[Q8Activations], n_cols: usize) -> Q8ActsX4 {
    assert!(acts.len() <= Q8K_ACTS_X4_NC);
    assert!(n_cols.is_multiple_of(Q8_0_BLOCK_ELEMS));
    let na = acts.len();
    let nb = n_cols / Q8_0_BLOCK_ELEMS;
    let mut qs = vec![0i8; nb * Q8_0_BLOCK_ELEMS * 4];
    let mut d = vec![0f32; nb * 4];
    for (a, act) in acts.iter().enumerate() {
        debug_assert_eq!(act.d.len(), nb);
        for b in 0..nb {
            let src = &act.q[b * Q8_0_BLOCK_ELEMS..(b + 1) * Q8_0_BLOCK_ELEMS];
            let dst = &mut qs[b * Q8_0_BLOCK_ELEMS * 4..(b + 1) * Q8_0_BLOCK_ELEMS * 4];
            for (c, run) in src.chunks_exact(8).enumerate() {
                dst[c * 32 + a * 8..c * 32 + a * 8 + 8].copy_from_slice(run);
            }
            d[b * 4 + a] = act.d[b];
        }
    }
    Q8ActsX4 {
        na,
        n_blocks: nb,
        qs,
        d,
    }
}

/// Whether [`gemm_q8_0x4_group_x4`] is the fast Q8_0 batch path on this
/// CPU: ARM i8mm with the interleave-8 layout (`ggml_gemm_q8_0_4x8_q8_0`).
#[inline]
pub fn q8_0x4_gemm_uses_acts_x4(interleave: usize) -> bool {
    #[cfg(target_arch = "aarch64")]
    {
        interleave == 8 && std::arch::is_aarch64_feature_detected!("i8mm")
    }
    #[cfg(not(target_arch = "aarch64"))]
    {
        let _ = interleave;
        false
    }
}

/// [`gemm_q8_0x4_group`] against a pre-interleaved activation quad;
/// interleave-8 packing only, quad prepared once per matmul by
/// [`prepare_q8_acts_x4`]. `out` is `[row][act]`: `out[r * tile.na + a]`.
pub fn gemm_q8_0x4_group_x4(
    packed: &[u8],
    group: usize,
    tile: &Q8ActsX4,
    n_cols: usize,
    interleave: usize,
    out: &mut [f32],
) {
    assert_eq!(
        interleave, 8,
        "the x4 GEMM only exists for interleave-8 packing"
    );
    assert_eq!(out.len(), Q8_0X4_NROWS * tile.na);
    assert!(n_cols.is_multiple_of(Q8_0_BLOCK_ELEMS));
    debug_assert_eq!(tile.n_blocks, n_cols / Q8_0_BLOCK_ELEMS);
    if tile.na == 0 {
        return;
    }
    let nb = n_cols / Q8_0_BLOCK_ELEMS;
    let off = group * nb * Q8_0X4_BLOCK_BYTES;
    let slice = &packed[off..off + nb * Q8_0X4_BLOCK_BYTES];

    #[cfg(target_arch = "aarch64")]
    if std::arch::is_aarch64_feature_detected!("i8mm") {
        unsafe {
            neon::gemm_q8_0x4_q8_0_neon_i8mm(slice, tile, n_cols, out);
        }
        return;
    }
    gemm_q8_0x4_acts_x4_scalar_8(slice, tile, n_cols, out);
}

/// Portable reference for the Q8_0 ×4 GEMM: the same math as
/// [`gemv_q8_0x4_q8_0_scalar`] at blocklen 8, per quad row, reading qs and
/// d out of the pre-interleaved [`Q8ActsX4`]. Bit-identical to running
/// that GEMV per activation, which is what the tests assert.
fn gemm_q8_0x4_acts_x4_scalar_8(packed: &[u8], tile: &Q8ActsX4, n_cols: usize, out: &mut [f32]) {
    let nb = n_cols / Q8_0_BLOCK_ELEMS;
    let blocklen = 8;
    let ncols = Q8_0X4_NROWS;
    let na = tile.na;
    let mut sumf = [[0f32; Q8_0X4_NROWS]; Q8K_ACTS_X4_NC];
    for l in 0..nb {
        let blk = &packed[l * Q8_0X4_BLOCK_BYTES..][..Q8_0X4_BLOCK_BYTES];
        let qs = &blk[8..];
        let q8 = &tile.qs[l * Q8_0_BLOCK_ELEMS * 4..][..Q8_0_BLOCK_ELEMS * 4];
        for a in 0..na {
            let da = tile.d[l * 4 + a];
            for k in 0..(Q8_0_BLOCK_ELEMS / blocklen) {
                for j in 0..ncols {
                    let mut sumi = 0i32;
                    for i in 0..blocklen {
                        let v0 = qs[k * ncols * blocklen + j * blocklen + i] as i8 as i32;
                        // Canonical q8 element `e` lives at run `e/8`, row
                        // `a`, lane `e%8` of the interleaved block.
                        let e = k * blocklen + i;
                        sumi += v0 * q8[(e / 8) * 32 + a * 8 + (e % 8)] as i32;
                    }
                    sumf[a][j] += sumi as f32 * f16_from_bytes(&blk[j * 2..]) * da;
                }
            }
        }
    }
    for j in 0..ncols {
        for (a, row) in sumf.iter().take(na).enumerate() {
            out[j * na + a] = row[j];
        }
    }
}

/// How many activations one [`gemm_q4_kx8_group`] pass keeps in flight.
///
/// Four is llama's shape for `ggml_gemm_q4_K_8x4_q8_K` (`q8_k_blocklen`),
/// and it is what the register file allows here: eight `uint8x16` weight
/// columns plus one activation's four `int8x16` and its accumulator pair
/// stay resident while the batch loop turns.
pub const Q4_KX8_GEMM_NC: usize = 4;

/// GEMM counterpart of [`gemv_q4_kx8_group`]: one row-group (8 rows)
/// against `acts.len()` activations at once.
///
/// Q4_K was the expensive omission. The GEMV repeats, *per activation*,
/// work that depends only on the weights: 16 f16 scale conversions, 8
/// `decode_scales_mins` calls and 16 `q4_cols` loads per 256-element
/// super-block. At batch 512 that is the same 6-bit scale decode run 512
/// times. Q8_0 already had `gemm_q8_0x4_group`; this is the same idea for
/// the format that carries every `*_Q4_K_M` checkpoint's FFN.
///
/// `out` is `[row][act]`: `out[r * acts.len() + j]`, matching
/// [`gemm_q8_0x4_group`] and what `WeightMatrix::apply_batch` writes.
pub fn gemm_q4_kx8_group(
    packed: &[u8],
    group: usize,
    acts: &[Q8KActivations],
    n_cols: usize,
    interleave: usize,
    out: &mut [f32],
) {
    assert_eq!(out.len(), Q4_KX8_NROWS * acts.len());
    assert!(n_cols.is_multiple_of(Q4_K_BLOCK_ELEMS));
    if acts.is_empty() {
        return;
    }
    let nb = n_cols / Q4_K_BLOCK_ELEMS;
    let off = group * nb * Q4_KX8_BLOCK_BYTES;
    let slice = &packed[off..off + nb * Q4_KX8_BLOCK_BYTES];

    #[cfg(target_arch = "aarch64")]
    if acts.len() <= Q4_KX8_GEMM_NC {
        if interleave == 8 && std::arch::is_aarch64_feature_detected!("i8mm") {
            // Compatibility entry: interleaves the quad here, once per call.
            // Batch callers should prepare the quad once per matmul and use
            // [`gemm_q4_kx8_group_x4`] for every row-group instead.
            let tile = prepare_q8_k_acts_x4(acts, n_cols);
            unsafe {
                neon::gemm_q4_kx8_q8_k_neon_i8mm(slice, &tile, n_cols, out);
            }
            return;
        }
        if interleave == 4 && std::arch::is_aarch64_feature_detected!("dotprod") {
            unsafe {
                neon::gemm_q4_kx8_q8_k_neon_sdot(slice, acts, n_cols, out);
            }
            return;
        }
    }
    // Portable fallback: the GEMV, once per activation. Same results,
    // none of the reuse.
    let mut tmp = [0f32; Q4_KX8_NROWS];
    for (j, act) in acts.iter().enumerate() {
        gemv_q4_kx8_q8_k(slice, act, n_cols, 1, interleave, &mut tmp);
        for (r, v) in tmp.iter().enumerate() {
            out[r * acts.len() + j] = *v;
        }
    }
}

/// A quad of up to [`Q8K_ACTS_X4_NC`] Q8_K activations, pre-interleaved into
/// the layout llama.cpp's `ggml_quantize_mat_q8_K_4x8` writes into
/// `block_q8_Kx4` (`ggml-cpu/repack.cpp`): every super-block's qs, the folded
/// `bsums` pairs, and the per-block per-row scales.
///
/// The i8mm GEMM consumes activations in this shape. Interleaving them once
/// per matmul — instead of once per (row-group, block) inside the kernel —
/// is the point: the old in-kernel repack was a scalar pass over
/// `rows/8 · batch · cols` bytes with a div and a mod per element, roughly
/// 4× the instruction count of the `vmmlaq_s32` math it fed.
/// Activations per [`Q8KActsX4`] quad (llama.cpp's `q8_k_blocklen`).
pub const Q8K_ACTS_X4_NC: usize = 4;

pub struct Q8KActsX4 {
    /// Real activations in the quad (≤ 4); rows `na..4` are zero padding.
    pub na: usize,
    /// Q8_K super-blocks per activation (`n_cols / 256`).
    pub n_blocks: usize,
    /// Interleaved quants, `n_blocks * 1024` long. Block `b`, 8-element run
    /// `c`, quad row `a`, lane `k` ↦
    /// `qs[b*1024 + c*32 + a*8 + k] = acts[a].q[b*256 + c*8 + k]`.
    pub qs: Vec<i8>,
    /// Folded `bsums` pairs, `n_blocks * 4 * 8` long:
    /// `bsums[(b*4 + a)*8 + i] = acts[a].bsums[b*16 + 2i] + acts[a].bsums[b*16 + 2i + 1]`.
    pub bsums: Vec<i16>,
    /// Activation scales, `n_blocks * 4` long: `d[b*4 + a] = acts[a].d[b]`.
    pub d: Vec<f32>,
}

/// Interleave a quad of activations for [`gemm_q4_kx8_group_x4`]
/// (llama.cpp `ggml_quantize_mat_q8_K_4x8`, minus the quantization we
/// already did). Zero-pads when `acts.len() < 4`, matching what the kernel's
/// in-loop repack used to emit. Available on every target so the portable
/// GEMM below — and the tests pinning the NEON kernel to it — run anywhere.
pub fn prepare_q8_k_acts_x4(acts: &[Q8KActivations], n_cols: usize) -> Q8KActsX4 {
    assert!(acts.len() <= Q8K_ACTS_X4_NC);
    assert!(n_cols.is_multiple_of(Q4_K_BLOCK_ELEMS));
    let na = acts.len();
    let nb = n_cols / Q4_K_BLOCK_ELEMS;
    let mut qs = vec![0i8; nb * Q4_K_BLOCK_ELEMS * 4];
    let mut bsums = vec![0i16; nb * 4 * 8];
    let mut d = vec![0f32; nb * 4];
    for (a, act) in acts.iter().enumerate() {
        debug_assert_eq!(act.n_blocks(), nb);
        for b in 0..nb {
            let src = &act.q[b * Q4_K_BLOCK_ELEMS..(b + 1) * Q4_K_BLOCK_ELEMS];
            let dst = &mut qs[b * Q4_K_BLOCK_ELEMS * 4..(b + 1) * Q4_K_BLOCK_ELEMS * 4];
            for (c, run) in src.chunks_exact(8).enumerate() {
                dst[c * 32 + a * 8..c * 32 + a * 8 + 8].copy_from_slice(run);
            }
            let src_bs = &act.bsums[b * 16..(b + 1) * 16];
            let dst_bs = &mut bsums[(b * 4 + a) * 8..(b * 4 + a) * 8 + 8];
            for (slot, pair) in dst_bs.iter_mut().zip(src_bs.chunks_exact(2)) {
                *slot = pair[0] + pair[1];
            }
            d[b * 4 + a] = act.d[b];
        }
    }
    Q8KActsX4 {
        na,
        n_blocks: nb,
        qs,
        bsums,
        d,
    }
}

/// Whether [`gemm_q4_kx8_group_x4`] is the fast Q4_K batch path on this CPU:
/// ARM i8mm with the interleave-8 layout. Everywhere else preparing the quad
/// buys nothing — x86 dispatches to AVX2 inside the per-activation GEMV — so
/// callers should keep using [`gemm_q4_kx8_group`] and skip the tiles.
#[inline]
pub fn q4_kx8_gemm_uses_acts_x4(interleave: usize) -> bool {
    #[cfg(target_arch = "aarch64")]
    {
        interleave == 8 && std::arch::is_aarch64_feature_detected!("i8mm")
    }
    #[cfg(not(target_arch = "aarch64"))]
    {
        let _ = interleave;
        false
    }
}

/// [`gemm_q4_kx8_group`] against a pre-interleaved activation quad.
///
/// Callers build the quad once per matmul with [`prepare_q8_k_acts_x4`] and
/// pass it to every row-group, hoisting what the i8mm kernel used to redo
/// `rows/8` times. Only the interleave-8 layout has this kernel; gate call
/// sites with [`q4_kx8_gemm_uses_acts_x4`].
///
/// `out` is `[row][act]` over the `tile.na` real activations:
/// `out[r * tile.na + a]`, matching [`gemm_q4_kx8_group`].
pub fn gemm_q4_kx8_group_x4(
    packed: &[u8],
    group: usize,
    tile: &Q8KActsX4,
    n_cols: usize,
    interleave: usize,
    out: &mut [f32],
) {
    assert_eq!(
        interleave, 8,
        "the x4 GEMM only exists for interleave-8 packing"
    );
    assert_eq!(out.len(), Q4_KX8_NROWS * tile.na);
    assert!(n_cols.is_multiple_of(Q4_K_BLOCK_ELEMS));
    debug_assert_eq!(tile.n_blocks, n_cols / Q4_K_BLOCK_ELEMS);
    if tile.na == 0 {
        return;
    }
    let nb = n_cols / Q4_K_BLOCK_ELEMS;
    let off = group * nb * Q4_KX8_BLOCK_BYTES;
    let slice = &packed[off..off + nb * Q4_KX8_BLOCK_BYTES];

    #[cfg(target_arch = "aarch64")]
    if std::arch::is_aarch64_feature_detected!("i8mm") {
        unsafe {
            neon::gemm_q4_kx8_q8_k_neon_i8mm(slice, tile, n_cols, out);
        }
        return;
    }
    gemm_q4_kx8_acts_x4_scalar_8(slice, tile, n_cols, out);
}

/// Portable reference for the ×4 GEMM: the same math as
/// [`gemv_q4_kx8_q8_k_scalar_8`], per quad row, reading qs / folded bsums /
/// d straight out of the pre-interleaved [`Q8KActsX4`]. Bit-identical to
/// running that GEMV per activation, which is what the tests assert.
fn gemm_q4_kx8_acts_x4_scalar_8(packed: &[u8], tile: &Q8KActsX4, n_cols: usize, out: &mut [f32]) {
    let nb = n_cols / Q4_K_BLOCK_ELEMS;
    let blocklen = 8;
    let ncols_interleaved = Q4_KX8_NROWS;
    let na = tile.na;
    let mut sumf = [[0f32; Q4_KX8_NROWS]; Q4_KX8_GEMM_NC];
    let mut sum_minf = [[0f32; Q4_KX8_NROWS]; Q4_KX8_GEMM_NC];
    for l in 0..nb {
        let blk = &packed[l * Q4_KX8_BLOCK_BYTES..][..Q4_KX8_BLOCK_BYTES];
        let d = &blk[0..16];
        let dmin = &blk[16..32];
        let scales = &blk[32..128];
        let qs = &blk[128..];
        let q8 = &tile.qs[l * Q4_K_BLOCK_ELEMS * 4..][..Q4_K_BLOCK_ELEMS * 4];

        let mut all_scales = [[0u8; 8]; 8];
        let mut all_mins = [[0u8; 8]; 8];
        for sb in 0..8 {
            decode_scales_mins(&scales[sb * 12..], &mut all_scales[sb], &mut all_mins[sb]);
        }

        for a in 0..na {
            let da = tile.d[l * 4 + a];
            let n_k = Q4_K_BLOCK_ELEMS / (2 * blocklen); // 16
            for k in 0..n_k {
                let sb_pair = k / 4;
                let sc0 = &all_scales[sb_pair * 2];
                let sc1 = &all_scales[sb_pair * 2 + 1];
                for j in 0..ncols_interleaved {
                    let mut sumi = 0i32;
                    for i in 0..blocklen {
                        let qbyte = qs[k * ncols_interleaved * blocklen + j * blocklen + i];
                        let v0 = (qbyte & 0x0F) as i32;
                        let v1 = (qbyte >> 4) as i32;
                        // Canonical q8 element `e` lives at run `e/8`, row
                        // `a`, lane `e%8` of the interleaved block.
                        let e0 = (k >> 2) * 64 + (k % 4) * blocklen + i;
                        let e1 = e0 + 32;
                        let a0 = q8[(e0 / 8) * 32 + a * 8 + (e0 % 8)] as i32;
                        let a1 = q8[(e1 / 8) * 32 + a * 8 + (e1 % 8)] as i32;
                        sumi += v0 * a0 * sc0[j] as i32 + v1 * a1 * sc1[j] as i32;
                    }
                    sumf[a][j] += sumi as f32 * f16_from_bytes(&d[j * 2..]) * da;
                }
            }
            for (sb, mins) in all_mins.iter().enumerate() {
                let bsum = tile.bsums[(l * 4 + a) * 8 + sb] as i32;
                for j in 0..ncols_interleaved {
                    sum_minf[a][j] +=
                        mins[j] as f32 * bsum as f32 * f16_from_bytes(&dmin[j * 2..]) * da;
                }
            }
        }
    }
    for j in 0..ncols_interleaved {
        for (a, row) in sumf.iter().take(na).enumerate() {
            out[j * na + a] = row[j] - sum_minf[a][j];
        }
    }
}

// ---------------------------------------------------------------------------
// Q5_K ×8 interleaved GEMV/GEMM (llama.cpp `block_q5_Kx8` / `ggml_gemm_q5_K_8x4`)
// ---------------------------------------------------------------------------

/// Bytes per interleaved `block_q5_Kx8` (8 × f16 d + 8 × f16 dmin + 96 scales +
/// 256 qh + 1024 qs).
pub const Q5_KX8_BLOCK_BYTES: usize = 1408;
/// Number of Q5_K rows packed into one interleaved block.
pub const Q5_KX8_NROWS: usize = 8;

/// Preferred qs/qh interleave width: 8 on x86 AVX2 and ARM i8mm
/// (`ggml_gemm_q5_K_8x8_q8_K`), 4 on DotProd-only NEON (`8x4`).
#[inline]
pub fn q5_kx8_interleave() -> usize {
    if cfg!(target_arch = "x86_64") {
        return 8;
    }
    #[cfg(target_arch = "aarch64")]
    {
        if std::arch::is_aarch64_feature_detected!("i8mm") {
            return 8;
        }
    }
    4
}

/// Pack eight canonical Q5_K super-blocks (same column-block index) into
/// one `block_q5_Kx8`. `interleave` is 4 (ARM DotProd) or 8 (x86 / ARM i8mm).
pub fn make_block_q5_kx8(
    rows: [&[u8]; Q5_KX8_NROWS],
    interleave: usize,
) -> [u8; Q5_KX8_BLOCK_BYTES] {
    debug_assert!(interleave == 4 || interleave == 8);
    for r in &rows {
        debug_assert_eq!(r.len(), Q5_K_BLOCK_BYTES);
    }
    let mut out = [0u8; Q5_KX8_BLOCK_BYTES];
    // d[8] at 0, dmin[8] at 16, scales[96] at 32, qh[256] at 128, qs[1024] at 384.
    for (i, row) in rows.iter().enumerate() {
        out[i * 2] = row[0];
        out[i * 2 + 1] = row[1];
        out[16 + i * 2] = row[2];
        out[16 + i * 2 + 1] = row[3];
    }

    let end = (Q5_K_BLOCK_ELEMS * 4) / interleave;
    let qs_out = &mut out[384..];
    for i in 0..end {
        let src_id = i % Q5_KX8_NROWS;
        let src_offset = (i / Q5_KX8_NROWS) * interleave;
        let dst_offset = i * interleave;
        let src_qs = &rows[src_id][48..176];
        qs_out[dst_offset..dst_offset + interleave]
            .copy_from_slice(&src_qs[src_offset..src_offset + interleave]);
    }

    let qh_end = end / 4;
    let qh_out = &mut out[128..384];
    for i in 0..qh_end {
        let src_id = i % Q5_KX8_NROWS;
        let src_offset = (i / Q5_KX8_NROWS) * interleave;
        let dst_offset = i * interleave;
        let src_qh = &rows[src_id][16..48];
        qh_out[dst_offset..dst_offset + interleave]
            .copy_from_slice(&src_qh[src_offset..src_offset + interleave]);
    }

    // Scale/min rearrangement (same 6-bit packing as Q4_Kx8).
    let mut s = [0u8; 8];
    let mut m = [0u8; 8];
    let scales_out = &mut out[32..128];

    for i in 0..4 {
        for j in 0..8 {
            let sc = &rows[j][4..16];
            s[j] = sc[i] & 63;
            m[j] = sc[i + 4] & 63;
        }
        let base = i * 12;
        scales_out[base] = (s[0] & 63) + ((s[4] & 48) << 2);
        scales_out[base + 1] = (s[1] & 63) + ((s[5] & 48) << 2);
        scales_out[base + 2] = (s[2] & 63) + ((s[6] & 48) << 2);
        scales_out[base + 3] = (s[3] & 63) + ((s[7] & 48) << 2);
        scales_out[base + 4] = (m[0] & 63) + ((m[4] & 48) << 2);
        scales_out[base + 5] = (m[1] & 63) + ((m[5] & 48) << 2);
        scales_out[base + 6] = (m[2] & 63) + ((m[6] & 48) << 2);
        scales_out[base + 7] = (m[3] & 63) + ((m[7] & 48) << 2);
        scales_out[base + 8] = (s[4] & 15) + ((m[4] & 15) << 4);
        scales_out[base + 9] = (s[5] & 15) + ((m[5] & 15) << 4);
        scales_out[base + 10] = (s[6] & 15) + ((m[6] & 15) << 4);
        scales_out[base + 11] = (s[7] & 15) + ((m[7] & 15) << 4);
    }

    for i in 0..4 {
        for j in 0..8 {
            let sc = &rows[j][4..16];
            s[j] = ((sc[i] & 192) >> 2) | (sc[i + 8] & 15);
            m[j] = ((sc[i + 4] & 192) >> 2) | ((sc[i + 8] & 240) >> 4);
        }
        let base = 48 + i * 12;
        scales_out[base] = (s[0] & 63) + ((s[4] & 48) << 2);
        scales_out[base + 1] = (s[1] & 63) + ((s[5] & 48) << 2);
        scales_out[base + 2] = (s[2] & 63) + ((s[6] & 48) << 2);
        scales_out[base + 3] = (s[3] & 63) + ((s[7] & 48) << 2);
        scales_out[base + 4] = (m[0] & 63) + ((m[4] & 48) << 2);
        scales_out[base + 5] = (m[1] & 63) + ((m[5] & 48) << 2);
        scales_out[base + 6] = (m[2] & 63) + ((m[6] & 48) << 2);
        scales_out[base + 7] = (m[3] & 63) + ((m[7] & 48) << 2);
        scales_out[base + 8] = (s[4] & 15) + ((m[4] & 15) << 4);
        scales_out[base + 9] = (s[5] & 15) + ((m[5] & 15) << 4);
        scales_out[base + 10] = (s[6] & 15) + ((m[6] & 15) << 4);
        scales_out[base + 11] = (s[7] & 15) + ((m[7] & 15) << 4);
    }

    out
}

/// Repack a full Q5_K matrix (row-major canonical blocks) into interleaved
/// `block_q5_Kx8` groups. Tail rows (not divisible by 8) are omitted.
pub fn pack_q5_k_matrix_x8(data: &[u8], rows: usize, cols: usize, interleave: usize) -> Vec<u8> {
    assert!(cols.is_multiple_of(Q5_K_BLOCK_ELEMS));
    let n_blocks = cols / Q5_K_BLOCK_ELEMS;
    let row_bytes = n_blocks * Q5_K_BLOCK_BYTES;
    assert_eq!(data.len(), rows * row_bytes);
    let n_groups = rows / Q5_KX8_NROWS;
    let mut out = Vec::with_capacity(n_groups * n_blocks * Q5_KX8_BLOCK_BYTES);
    for g in 0..n_groups {
        for b in 0..n_blocks {
            let mut row_refs: [&[u8]; Q5_KX8_NROWS] = [&[]; Q5_KX8_NROWS];
            for (r, slot) in row_refs.iter_mut().enumerate() {
                let base = (g * Q5_KX8_NROWS + r) * row_bytes + b * Q5_K_BLOCK_BYTES;
                *slot = &data[base..base + Q5_K_BLOCK_BYTES];
            }
            out.extend_from_slice(&make_block_q5_kx8(row_refs, interleave));
        }
    }
    out
}

/// Scalar GEMV for interleave=4 (`ggml_gemv_q5_K_8x4_q8_K_generic`).
fn gemv_q5_kx8_q8_k_scalar_4(
    packed: &[u8],
    act: &Q8KActivations,
    n_cols: usize,
    n_row_groups: usize,
    out: &mut [f32],
) {
    let nb = n_cols / Q5_K_BLOCK_ELEMS;
    let blocklen = 4;
    let ncols_interleaved = Q5_KX8_NROWS;
    debug_assert_eq!(act.n_blocks(), nb);
    debug_assert_eq!(out.len(), n_row_groups * ncols_interleaved);
    debug_assert_eq!(packed.len(), n_row_groups * nb * Q5_KX8_BLOCK_BYTES);

    for x in 0..n_row_groups {
        let mut sumf = [0f32; 8];
        let mut sum_minf = [0f32; 8];
        let group_off = x * nb * Q5_KX8_BLOCK_BYTES;
        for l in 0..nb {
            let blk = &packed[group_off + l * Q5_KX8_BLOCK_BYTES..][..Q5_KX8_BLOCK_BYTES];
            let d = &blk[0..16];
            let dmin = &blk[16..32];
            let scales = &blk[32..128];
            let qh = &blk[128..384];
            let qs = &blk[384..];
            let da = act.d[l];
            let q8 = &act.q[l * Q5_K_BLOCK_ELEMS..(l + 1) * Q5_K_BLOCK_ELEMS];
            let bsums = &act.bsums[l * 16..(l + 1) * 16];

            let mut all_scales = [[0u8; 8]; 8];
            let mut all_mins = [[0u8; 8]; 8];
            for sb in 0..8 {
                decode_scales_mins(&scales[sb * 12..], &mut all_scales[sb], &mut all_mins[sb]);
            }

            let n_k = Q5_K_BLOCK_ELEMS / (2 * blocklen); // 32
            for k in 0..n_k {
                let sb_pair = k / 8;
                let sc0 = &all_scales[sb_pair * 2];
                let sc1 = &all_scales[sb_pair * 2 + 1];
                let qh_shift = sb_pair * 2;
                for j in 0..ncols_interleaved {
                    let mut sumi = 0i32;
                    for i in 0..blocklen {
                        let b_qs_offset = k * ncols_interleaved * blocklen + j * blocklen + i;
                        let qh_idx = (k * blocklen + i) % 32;
                        let qh_chunk = qh_idx / blocklen;
                        let qh_pos = qh_idx % blocklen;
                        let b_qh_offset =
                            qh_chunk * (blocklen * ncols_interleaved) + j * blocklen + qh_pos;
                        let qh_val = qh[b_qh_offset];
                        let h0 = (qh_val >> qh_shift) & 1;
                        let h1 = (qh_val >> (qh_shift + 1)) & 1;
                        let v0 = ((qs[b_qs_offset] & 0x0F) | (h0 << 4)) as i32;
                        let v1 = ((qs[b_qs_offset] >> 4) | (h1 << 4)) as i32;
                        let a0 = q8[(k / 8) * 64 + (k % 8) * blocklen + i] as i32;
                        let a1 = q8[(k / 8) * 64 + (k % 8) * blocklen + i + 32] as i32;
                        sumi += v0 * a0 * sc0[j] as i32 + v1 * a1 * sc1[j] as i32;
                    }
                    sumf[j] += sumi as f32 * f16_from_bytes(&d[j * 2..]) * da;
                }
            }
            for sb in 0..8 {
                let mins = &all_mins[sb];
                let bsum = bsums[sb * 2] as i32 + bsums[sb * 2 + 1] as i32;
                for j in 0..ncols_interleaved {
                    sum_minf[j] +=
                        mins[j] as f32 * bsum as f32 * f16_from_bytes(&dmin[j * 2..]) * da;
                }
            }
        }
        let base = x * ncols_interleaved;
        for j in 0..ncols_interleaved {
            out[base + j] = sumf[j] - sum_minf[j];
        }
    }
}

/// Scalar GEMV for interleave=8 (`ggml_gemv_q5_K_8x8_q8_K_generic`).
fn gemv_q5_kx8_q8_k_scalar_8(
    packed: &[u8],
    act: &Q8KActivations,
    n_cols: usize,
    n_row_groups: usize,
    out: &mut [f32],
) {
    let nb = n_cols / Q5_K_BLOCK_ELEMS;
    let blocklen = 8;
    let ncols_interleaved = Q5_KX8_NROWS;
    debug_assert_eq!(act.n_blocks(), nb);
    debug_assert_eq!(out.len(), n_row_groups * ncols_interleaved);

    for x in 0..n_row_groups {
        let mut sumf = [0f32; 8];
        let mut sum_minf = [0f32; 8];
        let group_off = x * nb * Q5_KX8_BLOCK_BYTES;
        for l in 0..nb {
            let blk = &packed[group_off + l * Q5_KX8_BLOCK_BYTES..][..Q5_KX8_BLOCK_BYTES];
            let d = &blk[0..16];
            let dmin = &blk[16..32];
            let scales = &blk[32..128];
            let qh = &blk[128..384];
            let qs = &blk[384..];
            let da = act.d[l];
            let q8 = &act.q[l * Q5_K_BLOCK_ELEMS..(l + 1) * Q5_K_BLOCK_ELEMS];
            let bsums = &act.bsums[l * 16..(l + 1) * 16];

            let mut all_scales = [[0u8; 8]; 8];
            let mut all_mins = [[0u8; 8]; 8];
            for sb in 0..8 {
                decode_scales_mins(&scales[sb * 12..], &mut all_scales[sb], &mut all_mins[sb]);
            }

            let n_k = Q5_K_BLOCK_ELEMS / (2 * blocklen); // 16
            for k in 0..n_k {
                let sb_pair = k / 4;
                let sc0 = &all_scales[sb_pair * 2];
                let sc1 = &all_scales[sb_pair * 2 + 1];
                let qh_shift = sb_pair * 2;
                for j in 0..ncols_interleaved {
                    let mut sumi = 0i32;
                    for i in 0..blocklen {
                        let b_qs_offset = k * ncols_interleaved * blocklen + j * blocklen + i;
                        let qh_idx = (k * blocklen + i) % 32;
                        let qh_chunk = qh_idx / blocklen;
                        let qh_pos = qh_idx % blocklen;
                        let b_qh_offset =
                            qh_chunk * (blocklen * ncols_interleaved) + j * blocklen + qh_pos;
                        let qh_val = qh[b_qh_offset];
                        let h0 = (qh_val >> qh_shift) & 1;
                        let h1 = (qh_val >> (qh_shift + 1)) & 1;
                        let v0 = ((qs[b_qs_offset] & 0x0F) | (h0 << 4)) as i32;
                        let v1 = ((qs[b_qs_offset] >> 4) | (h1 << 4)) as i32;
                        let a0 = q8[(k >> 2) * 64 + (k % 4) * blocklen + i] as i32;
                        let a1 = q8[(k >> 2) * 64 + (k % 4) * blocklen + i + 32] as i32;
                        sumi += v0 * a0 * sc0[j] as i32 + v1 * a1 * sc1[j] as i32;
                    }
                    sumf[j] += sumi as f32 * f16_from_bytes(&d[j * 2..]) * da;
                }
            }
            for sb in 0..8 {
                let mins = &all_mins[sb];
                let bsum = bsums[sb * 2] as i32 + bsums[sb * 2 + 1] as i32;
                for j in 0..ncols_interleaved {
                    sum_minf[j] +=
                        mins[j] as f32 * bsum as f32 * f16_from_bytes(&dmin[j * 2..]) * da;
                }
            }
        }
        let base = x * ncols_interleaved;
        for j in 0..ncols_interleaved {
            out[base + j] = sumf[j] - sum_minf[j];
        }
    }
}

/// GEMV: interleaved Q5_K weights × Q8_K activation → `n_row_groups * 8` f32s.
pub fn gemv_q5_kx8_q8_k(
    packed: &[u8],
    act: &Q8KActivations,
    n_cols: usize,
    n_row_groups: usize,
    interleave: usize,
    out: &mut [f32],
) {
    assert!(n_cols.is_multiple_of(Q5_K_BLOCK_ELEMS));
    assert_eq!(out.len(), n_row_groups * Q5_KX8_NROWS);
    match interleave {
        4 => {
            #[cfg(target_arch = "aarch64")]
            {
                if std::arch::is_aarch64_feature_detected!("dotprod") {
                    unsafe {
                        neon::gemv_q5_kx8_q8_k_neon_sdot(packed, act, n_cols, n_row_groups, out);
                    }
                    return;
                }
            }
            gemv_q5_kx8_q8_k_scalar_4(packed, act, n_cols, n_row_groups, out);
        }
        8 => {
            #[cfg(target_arch = "aarch64")]
            {
                if std::arch::is_aarch64_feature_detected!("dotprod") {
                    unsafe {
                        neon::gemv_q5_kx8_q8_k_neon_8x8(packed, act, n_cols, n_row_groups, out);
                    }
                    return;
                }
            }
            gemv_q5_kx8_q8_k_scalar_8(packed, act, n_cols, n_row_groups, out);
        }
        _ => panic!("q5_kx8 interleave must be 4 or 8, got {interleave}"),
    }
}

/// One row-group (8 outputs) starting at `group` within a packed Q5_K matrix.
#[inline]
pub fn gemv_q5_kx8_group(
    packed: &[u8],
    group: usize,
    act: &Q8KActivations,
    n_cols: usize,
    interleave: usize,
    out8: &mut [f32],
) {
    debug_assert_eq!(out8.len(), Q5_KX8_NROWS);
    let nb = n_cols / Q5_K_BLOCK_ELEMS;
    let off = group * nb * Q5_KX8_BLOCK_BYTES;
    let slice = &packed[off..off + nb * Q5_KX8_BLOCK_BYTES];
    gemv_q5_kx8_q8_k(slice, act, n_cols, 1, interleave, out8);
}

/// How many activations one [`gemm_q5_kx8_group`] pass keeps in flight.
pub const Q5_KX8_GEMM_NC: usize = 4;

/// GEMM counterpart of [`gemv_q5_kx8_group`]: one row-group (8 rows)
/// against `acts.len()` activations at once. `out` is `[row][act]`:
/// `out[r * acts.len() + j]`.
///
/// Weight-side decode (scales/mins/qh/qs addressing) is amortized across
/// the activation tile — same motivation as llama `ggml_gemm_q5_K_*`.
pub fn gemm_q5_kx8_group(
    packed: &[u8],
    group: usize,
    acts: &[Q8KActivations],
    n_cols: usize,
    interleave: usize,
    out: &mut [f32],
) {
    assert_eq!(out.len(), Q5_KX8_NROWS * acts.len());
    assert!(n_cols.is_multiple_of(Q5_K_BLOCK_ELEMS));
    if acts.is_empty() {
        return;
    }
    let nb = n_cols / Q5_K_BLOCK_ELEMS;
    let off = group * nb * Q5_KX8_BLOCK_BYTES;
    let slice = &packed[off..off + nb * Q5_KX8_BLOCK_BYTES];
    #[cfg(target_arch = "aarch64")]
    {
        if acts.len() <= Q5_KX8_GEMM_NC {
            if interleave == 8 && std::arch::is_aarch64_feature_detected!("i8mm") {
                // Compatibility entry: interleaves the quad here, once per
                // call. Batch callers should prepare the quad once per
                // matmul and use [`gemm_q5_kx8_group_x4`] instead.
                let tile = prepare_q8_k_acts_x4(acts, n_cols);
                unsafe {
                    neon::gemm_q5_kx8_q8_k_neon_i8mm(slice, &tile, n_cols, out);
                }
                return;
            }
            if interleave == 4 && std::arch::is_aarch64_feature_detected!("dotprod") {
                unsafe {
                    neon::gemm_q5_kx8_q8_k_neon_sdot(slice, acts, n_cols, out);
                }
                return;
            }
        }
    }
    match interleave {
        4 => gemm_q5_kx8_q8_k_scalar_4(slice, acts, n_cols, out),
        8 => gemm_q5_kx8_q8_k_scalar_8(slice, acts, n_cols, out),
        _ => panic!("q5_kx8 interleave must be 4 or 8, got {interleave}"),
    }
}

/// Whether [`gemm_q5_kx8_group_x4`] is the fast Q5_K batch path on this CPU:
/// ARM i8mm with the interleave-8 layout (`ggml_gemm_q5_K_8x8_q8_K`).
#[inline]
pub fn q5_kx8_gemm_uses_acts_x4(interleave: usize) -> bool {
    #[cfg(target_arch = "aarch64")]
    {
        interleave == 8 && std::arch::is_aarch64_feature_detected!("i8mm")
    }
    #[cfg(not(target_arch = "aarch64"))]
    {
        let _ = interleave;
        false
    }
}

/// [`gemm_q5_kx8_group`] against a pre-interleaved activation quad; the
/// Q5_K counterpart of [`gemm_q4_kx8_group_x4`], with the same contract:
/// interleave-8 packing only, quad prepared once per matmul by
/// [`prepare_q8_k_acts_x4`], `out[r * tile.na + a]`.
pub fn gemm_q5_kx8_group_x4(
    packed: &[u8],
    group: usize,
    tile: &Q8KActsX4,
    n_cols: usize,
    interleave: usize,
    out: &mut [f32],
) {
    assert_eq!(
        interleave, 8,
        "the x4 GEMM only exists for interleave-8 packing"
    );
    assert_eq!(out.len(), Q5_KX8_NROWS * tile.na);
    assert!(n_cols.is_multiple_of(Q5_K_BLOCK_ELEMS));
    debug_assert_eq!(tile.n_blocks, n_cols / Q5_K_BLOCK_ELEMS);
    if tile.na == 0 {
        return;
    }
    let nb = n_cols / Q5_K_BLOCK_ELEMS;
    let off = group * nb * Q5_KX8_BLOCK_BYTES;
    let slice = &packed[off..off + nb * Q5_KX8_BLOCK_BYTES];

    #[cfg(target_arch = "aarch64")]
    if std::arch::is_aarch64_feature_detected!("i8mm") {
        unsafe {
            neon::gemm_q5_kx8_q8_k_neon_i8mm(slice, tile, n_cols, out);
        }
        return;
    }
    gemm_q5_kx8_acts_x4_scalar_8(slice, tile, n_cols, out);
}

/// Portable reference for the Q5_K ×4 GEMM: the same math as
/// [`gemv_q5_kx8_q8_k_scalar_8`], per quad row, reading qs / qh / folded
/// bsums / d out of the pre-interleaved [`Q8KActsX4`]. Bit-identical to
/// running that GEMV per activation, which is what the tests assert.
fn gemm_q5_kx8_acts_x4_scalar_8(packed: &[u8], tile: &Q8KActsX4, n_cols: usize, out: &mut [f32]) {
    let nb = n_cols / Q5_K_BLOCK_ELEMS;
    let blocklen = 8;
    let ncols_interleaved = Q5_KX8_NROWS;
    let na = tile.na;
    let mut sumf = [[0f32; Q5_KX8_NROWS]; Q5_KX8_GEMM_NC];
    let mut sum_minf = [[0f32; Q5_KX8_NROWS]; Q5_KX8_GEMM_NC];
    for l in 0..nb {
        let blk = &packed[l * Q5_KX8_BLOCK_BYTES..][..Q5_KX8_BLOCK_BYTES];
        let d = &blk[0..16];
        let dmin = &blk[16..32];
        let scales = &blk[32..128];
        let qh = &blk[128..384];
        let qs = &blk[384..];
        let q8 = &tile.qs[l * Q5_K_BLOCK_ELEMS * 4..][..Q5_K_BLOCK_ELEMS * 4];

        let mut all_scales = [[0u8; 8]; 8];
        let mut all_mins = [[0u8; 8]; 8];
        for sb in 0..8 {
            decode_scales_mins(&scales[sb * 12..], &mut all_scales[sb], &mut all_mins[sb]);
        }

        for a in 0..na {
            let da = tile.d[l * 4 + a];
            let n_k = Q5_K_BLOCK_ELEMS / (2 * blocklen); // 16
            for k in 0..n_k {
                let sb_pair = k / 4;
                let sc0 = &all_scales[sb_pair * 2];
                let sc1 = &all_scales[sb_pair * 2 + 1];
                let qh_shift = sb_pair * 2;
                for j in 0..ncols_interleaved {
                    let mut sumi = 0i32;
                    for i in 0..blocklen {
                        let b_qs_offset = k * ncols_interleaved * blocklen + j * blocklen + i;
                        let qh_idx = (k * blocklen + i) % 32;
                        let qh_chunk = qh_idx / blocklen;
                        let qh_pos = qh_idx % blocklen;
                        let b_qh_offset =
                            qh_chunk * (blocklen * ncols_interleaved) + j * blocklen + qh_pos;
                        let qh_val = qh[b_qh_offset];
                        let h0 = (qh_val >> qh_shift) & 1;
                        let h1 = (qh_val >> (qh_shift + 1)) & 1;
                        let v0 = ((qs[b_qs_offset] & 0x0F) | (h0 << 4)) as i32;
                        let v1 = ((qs[b_qs_offset] >> 4) | (h1 << 4)) as i32;
                        // Canonical q8 element `e` lives at run `e/8`, row
                        // `a`, lane `e%8` of the interleaved block.
                        let e0 = (k >> 2) * 64 + (k % 4) * blocklen + i;
                        let e1 = e0 + 32;
                        let a0 = q8[(e0 / 8) * 32 + a * 8 + (e0 % 8)] as i32;
                        let a1 = q8[(e1 / 8) * 32 + a * 8 + (e1 % 8)] as i32;
                        sumi += v0 * a0 * sc0[j] as i32 + v1 * a1 * sc1[j] as i32;
                    }
                    sumf[a][j] += sumi as f32 * f16_from_bytes(&d[j * 2..]) * da;
                }
            }
            for (sb, mins) in all_mins.iter().enumerate() {
                let bsum = tile.bsums[(l * 4 + a) * 8 + sb] as i32;
                for j in 0..ncols_interleaved {
                    sum_minf[a][j] +=
                        mins[j] as f32 * bsum as f32 * f16_from_bytes(&dmin[j * 2..]) * da;
                }
            }
        }
    }
    for j in 0..ncols_interleaved {
        for (a, row) in sumf.iter().take(na).enumerate() {
            out[j * na + a] = row[j] - sum_minf[a][j];
        }
    }
}

fn gemm_q5_kx8_q8_k_scalar_4(
    packed: &[u8],
    acts: &[Q8KActivations],
    n_cols: usize,
    out: &mut [f32],
) {
    let na = acts.len();
    let nb = n_cols / Q5_K_BLOCK_ELEMS;
    let blocklen = 4;
    let ncols = Q5_KX8_NROWS;
    out.fill(0.0);
    let mut sum_minf = vec![0f32; ncols * na];
    for l in 0..nb {
        let blk = &packed[l * Q5_KX8_BLOCK_BYTES..][..Q5_KX8_BLOCK_BYTES];
        let d = &blk[0..16];
        let dmin = &blk[16..32];
        let scales = &blk[32..128];
        let qh = &blk[128..384];
        let qs = &blk[384..];
        let mut all_scales = [[0u8; 8]; 8];
        let mut all_mins = [[0u8; 8]; 8];
        for sb in 0..8 {
            decode_scales_mins(&scales[sb * 12..], &mut all_scales[sb], &mut all_mins[sb]);
        }
        let n_k = Q5_K_BLOCK_ELEMS / (2 * blocklen);
        for (a, act) in acts.iter().enumerate() {
            let da = act.d[l];
            let q8 = &act.q[l * Q5_K_BLOCK_ELEMS..(l + 1) * Q5_K_BLOCK_ELEMS];
            let bsums = &act.bsums[l * 16..(l + 1) * 16];
            for k in 0..n_k {
                let sb_pair = k / 8;
                let sc0 = &all_scales[sb_pair * 2];
                let sc1 = &all_scales[sb_pair * 2 + 1];
                let qh_shift = sb_pair * 2;
                for j in 0..ncols {
                    let mut sumi = 0i32;
                    for i in 0..blocklen {
                        let b_qs_offset = k * ncols * blocklen + j * blocklen + i;
                        let qh_idx = (k * blocklen + i) % 32;
                        let qh_chunk = qh_idx / blocklen;
                        let qh_pos = qh_idx % blocklen;
                        let b_qh_offset = qh_chunk * (blocklen * ncols) + j * blocklen + qh_pos;
                        let qh_val = qh[b_qh_offset];
                        let h0 = (qh_val >> qh_shift) & 1;
                        let h1 = (qh_val >> (qh_shift + 1)) & 1;
                        let v0 = ((qs[b_qs_offset] & 0x0F) | (h0 << 4)) as i32;
                        let v1 = ((qs[b_qs_offset] >> 4) | (h1 << 4)) as i32;
                        let a0 = q8[(k / 8) * 64 + (k % 8) * blocklen + i] as i32;
                        let a1 = q8[(k / 8) * 64 + (k % 8) * blocklen + i + 32] as i32;
                        sumi += v0 * a0 * sc0[j] as i32 + v1 * a1 * sc1[j] as i32;
                    }
                    out[j * na + a] += sumi as f32 * f16_from_bytes(&d[j * 2..]) * da;
                }
            }
            for sb in 0..8 {
                let mins = &all_mins[sb];
                let bsum = bsums[sb * 2] as i32 + bsums[sb * 2 + 1] as i32;
                for j in 0..ncols {
                    sum_minf[j * na + a] +=
                        mins[j] as f32 * bsum as f32 * f16_from_bytes(&dmin[j * 2..]) * da;
                }
            }
        }
    }
    for i in 0..ncols * na {
        out[i] -= sum_minf[i];
    }
}

fn gemm_q5_kx8_q8_k_scalar_8(
    packed: &[u8],
    acts: &[Q8KActivations],
    n_cols: usize,
    out: &mut [f32],
) {
    let na = acts.len();
    let nb = n_cols / Q5_K_BLOCK_ELEMS;
    let blocklen = 8;
    let ncols = Q5_KX8_NROWS;
    out.fill(0.0);
    let mut sum_minf = vec![0f32; ncols * na];
    for l in 0..nb {
        let blk = &packed[l * Q5_KX8_BLOCK_BYTES..][..Q5_KX8_BLOCK_BYTES];
        let d = &blk[0..16];
        let dmin = &blk[16..32];
        let scales = &blk[32..128];
        let qh = &blk[128..384];
        let qs = &blk[384..];
        let mut all_scales = [[0u8; 8]; 8];
        let mut all_mins = [[0u8; 8]; 8];
        for sb in 0..8 {
            decode_scales_mins(&scales[sb * 12..], &mut all_scales[sb], &mut all_mins[sb]);
        }
        let n_k = Q5_K_BLOCK_ELEMS / (2 * blocklen);
        for (a, act) in acts.iter().enumerate() {
            let da = act.d[l];
            let q8 = &act.q[l * Q5_K_BLOCK_ELEMS..(l + 1) * Q5_K_BLOCK_ELEMS];
            let bsums = &act.bsums[l * 16..(l + 1) * 16];
            for k in 0..n_k {
                let sb_pair = k / 4;
                let sc0 = &all_scales[sb_pair * 2];
                let sc1 = &all_scales[sb_pair * 2 + 1];
                let qh_shift = sb_pair * 2;
                for j in 0..ncols {
                    let mut sumi = 0i32;
                    for i in 0..blocklen {
                        let b_qs_offset = k * ncols * blocklen + j * blocklen + i;
                        let qh_idx = (k * blocklen + i) % 32;
                        let qh_chunk = qh_idx / blocklen;
                        let qh_pos = qh_idx % blocklen;
                        let b_qh_offset = qh_chunk * (blocklen * ncols) + j * blocklen + qh_pos;
                        let qh_val = qh[b_qh_offset];
                        let h0 = (qh_val >> qh_shift) & 1;
                        let h1 = (qh_val >> (qh_shift + 1)) & 1;
                        let v0 = ((qs[b_qs_offset] & 0x0F) | (h0 << 4)) as i32;
                        let v1 = ((qs[b_qs_offset] >> 4) | (h1 << 4)) as i32;
                        let a0 = q8[(k >> 2) * 64 + (k % 4) * blocklen + i] as i32;
                        let a1 = q8[(k >> 2) * 64 + (k % 4) * blocklen + i + 32] as i32;
                        sumi += v0 * a0 * sc0[j] as i32 + v1 * a1 * sc1[j] as i32;
                    }
                    out[j * na + a] += sumi as f32 * f16_from_bytes(&d[j * 2..]) * da;
                }
            }
            for sb in 0..8 {
                let mins = &all_mins[sb];
                let bsum = bsums[sb * 2] as i32 + bsums[sb * 2 + 1] as i32;
                for j in 0..ncols {
                    sum_minf[j * na + a] +=
                        mins[j] as f32 * bsum as f32 * f16_from_bytes(&dmin[j * 2..]) * da;
                }
            }
        }
    }
    for i in 0..ncols * na {
        out[i] -= sum_minf[i];
    }
}

// ---------------------------------------------------------------------------
// Q6_K ×8 interleaved GEMV/GEMM (llama.cpp `block_q6_Kx8`)
// ---------------------------------------------------------------------------

/// Bytes per interleaved `block_q6_Kx8` (8×f16 d + 128 scales + 1024 ql + 512 qh).
pub const Q6_KX8_BLOCK_BYTES: usize = 1680;
/// Number of Q6_K rows packed into one interleaved block.
pub const Q6_KX8_NROWS: usize = 8;

/// Preferred ql/qh interleave width: 8 on x86 AVX2 and ARM i8mm
/// (`ggml_gemm_q6_K_8x8_q8_K`), 4 on DotProd-only NEON.
#[inline]
pub fn q6_kx8_interleave() -> usize {
    if cfg!(target_arch = "x86_64") {
        return 8;
    }
    #[cfg(target_arch = "aarch64")]
    {
        if std::arch::is_aarch64_feature_detected!("i8mm") {
            return 8;
        }
    }
    4
}

/// Pack eight canonical Q6_K super-blocks into one `block_q6_Kx8`.
pub fn make_block_q6_kx8(
    rows: [&[u8]; Q6_KX8_NROWS],
    interleave: usize,
) -> [u8; Q6_KX8_BLOCK_BYTES] {
    debug_assert!(interleave == 4 || interleave == 8);
    for r in &rows {
        debug_assert_eq!(r.len(), Q6_K_BLOCK_BYTES);
    }
    let mut out = [0u8; Q6_KX8_BLOCK_BYTES];
    // d[8] @0, scales[128] @16, ql[1024] @144, qh[512] @1168
    for (i, row) in rows.iter().enumerate() {
        out[i * 2] = row[208];
        out[i * 2 + 1] = row[209];
    }
    let end_ls = (Q6_K_BLOCK_ELEMS * 4) / interleave;
    let ql_out = &mut out[144..1168];
    for i in 0..end_ls {
        let src_id = i % Q6_KX8_NROWS;
        let src_offset = (i / Q6_KX8_NROWS) * interleave;
        let dst_offset = i * interleave;
        let src_ql = &rows[src_id][0..128];
        ql_out[dst_offset..dst_offset + interleave]
            .copy_from_slice(&src_ql[src_offset..src_offset + interleave]);
    }
    let end_hs = end_ls / 2;
    let qh_out = &mut out[1168..];
    for i in 0..end_hs {
        let src_id = i % Q6_KX8_NROWS;
        let src_offset = (i / Q6_KX8_NROWS) * interleave;
        let dst_offset = i * interleave;
        let src_qh = &rows[src_id][128..192];
        qh_out[dst_offset..dst_offset + interleave]
            .copy_from_slice(&src_qh[src_offset..src_offset + interleave]);
    }
    let n_scales = Q6_K_BLOCK_ELEMS / 16;
    let scales_out = &mut out[16..144];
    for i in 0..Q6_KX8_NROWS {
        let src_sc = &rows[i][192..208];
        for j in 0..n_scales {
            scales_out[j * Q6_KX8_NROWS + i] = src_sc[j];
        }
    }
    out
}

pub fn pack_q6_k_matrix_x8(data: &[u8], rows: usize, cols: usize, interleave: usize) -> Vec<u8> {
    // Rows past the last full group of 8 are left canonical, same as the
    // other pack_*_matrix helpers; callers dot them row-by-row.
    assert!(cols.is_multiple_of(Q6_K_BLOCK_ELEMS));
    let row_bytes = (cols / Q6_K_BLOCK_ELEMS) * Q6_K_BLOCK_BYTES;
    assert_eq!(data.len(), rows * row_bytes);
    let n_blocks = cols / Q6_K_BLOCK_ELEMS;
    let n_groups = rows / Q6_KX8_NROWS;
    let mut out = Vec::with_capacity(n_groups * n_blocks * Q6_KX8_BLOCK_BYTES);
    for g in 0..n_groups {
        for b in 0..n_blocks {
            let mut row_refs: [&[u8]; Q6_KX8_NROWS] = [&[]; Q6_KX8_NROWS];
            for (r, slot) in row_refs.iter_mut().enumerate() {
                let base = (g * Q6_KX8_NROWS + r) * row_bytes + b * Q6_K_BLOCK_BYTES;
                *slot = &data[base..base + Q6_K_BLOCK_BYTES];
            }
            out.extend_from_slice(&make_block_q6_kx8(row_refs, interleave));
        }
    }
    out
}

fn gemv_q6_kx8_q8_k_scalar(
    packed: &[u8],
    act: &Q8KActivations,
    n_cols: usize,
    n_row_groups: usize,
    blocklen: usize,
    out: &mut [f32],
) {
    let nb = n_cols / Q6_K_BLOCK_ELEMS;
    let ncols = Q6_KX8_NROWS;
    let blocks_per_half = 64 / blocklen;
    debug_assert_eq!(act.n_blocks(), nb);
    debug_assert_eq!(out.len(), n_row_groups * ncols);
    for x in 0..n_row_groups {
        let mut sumf = [0f32; 8];
        let group_off = x * nb * Q6_KX8_BLOCK_BYTES;
        for l in 0..nb {
            let blk = &packed[group_off + l * Q6_KX8_BLOCK_BYTES..][..Q6_KX8_BLOCK_BYTES];
            let d = &blk[0..16];
            let scales = &blk[16..144];
            let ql = &blk[144..1168];
            let qh = &blk[1168..];
            let da = act.d[l];
            let q8 = &act.q[l * Q6_K_BLOCK_ELEMS..(l + 1) * Q6_K_BLOCK_ELEMS];
            for k in 0..(Q6_K_BLOCK_ELEMS / (2 * blocklen)) {
                let base_l = (k / blocks_per_half) * 128 + (k % blocks_per_half) * blocklen;
                let base_h = base_l + 64;
                let scale_idx_l = base_l / 16;
                let scale_idx_h = base_h / 16;
                let qh_shift_l = ((base_l % 128) / 32) * 2;
                let qh_shift_h = ((base_h % 128) / 32) * 2;
                let qh_half_l = (base_l / 128) * 32;
                let qh_half_h = (base_h / 128) * 32;
                for j in 0..ncols {
                    let scale_l = scales[scale_idx_l * ncols + j] as i8 as i32;
                    let scale_h = scales[scale_idx_h * ncols + j] as i8 as i32;
                    let mut sumi_l = 0i32;
                    let mut sumi_h = 0i32;
                    for i in 0..blocklen {
                        let ql_pos = k * ncols * blocklen + j * blocklen + i;
                        let l_4 = (ql[ql_pos] & 0x0F) as i32;
                        let hi_4 = ((ql[ql_pos] >> 4) & 0x0F) as i32;
                        let qh_idx_l = qh_half_l + ((base_l + i) % 32);
                        let qh_chunk_l = qh_idx_l / blocklen;
                        let qh_pos_l = qh_idx_l % blocklen;
                        let qh_offset_l = qh_chunk_l * (blocklen * ncols) + j * blocklen + qh_pos_l;
                        let hi_2_l = ((qh[qh_offset_l] >> qh_shift_l) & 0x3) as i32;
                        let qh_idx_h = qh_half_h + ((base_h + i) % 32);
                        let qh_chunk_h = qh_idx_h / blocklen;
                        let qh_pos_h = qh_idx_h % blocklen;
                        let qh_offset_h = qh_chunk_h * (blocklen * ncols) + j * blocklen + qh_pos_h;
                        let hi_2_h = ((qh[qh_offset_h] >> qh_shift_h) & 0x3) as i32;
                        let q_l = ((hi_2_l << 4) | l_4) - 32;
                        let q_h = ((hi_2_h << 4) | hi_4) - 32;
                        sumi_l += q_l * (q8[base_l + i] as i32);
                        sumi_h += q_h * (q8[base_h + i] as i32);
                    }
                    sumf[j] += (sumi_l * scale_l + sumi_h * scale_h) as f32
                        * f16_from_bytes(&d[j * 2..])
                        * da;
                }
            }
        }
        let base = x * ncols;
        out[base..base + ncols].copy_from_slice(&sumf);
    }
}

pub fn gemv_q6_kx8_q8_k(
    packed: &[u8],
    act: &Q8KActivations,
    n_cols: usize,
    n_row_groups: usize,
    interleave: usize,
    out: &mut [f32],
) {
    assert_eq!(out.len(), n_row_groups * Q6_KX8_NROWS);
    match interleave {
        4 => gemv_q6_kx8_q8_k_scalar(packed, act, n_cols, n_row_groups, 4, out),
        8 => {
            #[cfg(target_arch = "aarch64")]
            {
                if std::arch::is_aarch64_feature_detected!("dotprod") {
                    unsafe {
                        neon::gemv_q6_kx8_q8_k_neon_8x8(packed, act, n_cols, n_row_groups, out);
                    }
                    return;
                }
            }
            gemv_q6_kx8_q8_k_scalar(packed, act, n_cols, n_row_groups, 8, out)
        }
        _ => panic!("q6_kx8 interleave must be 4 or 8, got {interleave}"),
    }
}

pub fn gemv_q6_kx8_group(
    packed: &[u8],
    group: usize,
    act: &Q8KActivations,
    n_cols: usize,
    interleave: usize,
    out8: &mut [f32],
) {
    debug_assert_eq!(out8.len(), Q6_KX8_NROWS);
    let nb = n_cols / Q6_K_BLOCK_ELEMS;
    let off = group * nb * Q6_KX8_BLOCK_BYTES;
    let slice = &packed[off..off + nb * Q6_KX8_BLOCK_BYTES];
    gemv_q6_kx8_q8_k(slice, act, n_cols, 1, interleave, out8);
}

pub const Q6_KX8_GEMM_NC: usize = 8;

/// Multi-act GEMM for one Q6_Kx8 row-group; weight decode amortized across acts.
pub fn gemm_q6_kx8_group(
    packed: &[u8],
    group: usize,
    acts: &[Q8KActivations],
    n_cols: usize,
    interleave: usize,
    out: &mut [f32],
) {
    assert_eq!(out.len(), Q6_KX8_NROWS * acts.len());
    assert!(n_cols.is_multiple_of(Q6_K_BLOCK_ELEMS));
    if acts.is_empty() {
        return;
    }
    let nb = n_cols / Q6_K_BLOCK_ELEMS;
    let off = group * nb * Q6_KX8_BLOCK_BYTES;
    let slice = &packed[off..off + nb * Q6_KX8_BLOCK_BYTES];
    #[cfg(target_arch = "aarch64")]
    {
        if interleave == 8
            && acts.len() <= Q8K_ACTS_X4_NC
            && std::arch::is_aarch64_feature_detected!("i8mm")
        {
            // Compatibility entry: interleaves the quad here, once per
            // call. Batch callers should prepare the quad once per matmul
            // and use [`gemm_q6_kx8_group_x4`] instead.
            let tile = prepare_q8_k_acts_x4(acts, n_cols);
            unsafe {
                neon::gemm_q6_kx8_q8_k_neon_i8mm(slice, &tile, n_cols, out);
            }
            return;
        }
    }
    let blocklen = interleave;
    assert!(blocklen == 4 || blocklen == 8);
    let na = acts.len();
    let ncols = Q6_KX8_NROWS;
    let blocks_per_half = 64 / blocklen;
    out.fill(0.0);
    for l in 0..nb {
        let blk = &slice[l * Q6_KX8_BLOCK_BYTES..][..Q6_KX8_BLOCK_BYTES];
        let d = &blk[0..16];
        let scales = &blk[16..144];
        let ql = &blk[144..1168];
        let qh = &blk[1168..];
        let mut d_f = [0f32; 8];
        for j in 0..8 {
            d_f[j] = f16_from_bytes(&d[j * 2..]);
        }
        for k in 0..(Q6_K_BLOCK_ELEMS / (2 * blocklen)) {
            let base_l = (k / blocks_per_half) * 128 + (k % blocks_per_half) * blocklen;
            let base_h = base_l + 64;
            let scale_idx_l = base_l / 16;
            let scale_idx_h = base_h / 16;
            let qh_shift_l = ((base_l % 128) / 32) * 2;
            let qh_shift_h = ((base_h % 128) / 32) * 2;
            let qh_half_l = (base_l / 128) * 32;
            let qh_half_h = (base_h / 128) * 32;
            for j in 0..ncols {
                let scale_l = scales[scale_idx_l * ncols + j] as i8 as i32;
                let scale_h = scales[scale_idx_h * ncols + j] as i8 as i32;
                // Decode 8 weight quants for this (k,j) once.
                let mut q_l = [0i32; 8];
                let mut q_h = [0i32; 8];
                for i in 0..blocklen {
                    let ql_pos = k * ncols * blocklen + j * blocklen + i;
                    let l_4 = (ql[ql_pos] & 0x0F) as i32;
                    let hi_4 = ((ql[ql_pos] >> 4) & 0x0F) as i32;
                    let qh_idx_l = qh_half_l + ((base_l + i) % 32);
                    let qh_chunk_l = qh_idx_l / blocklen;
                    let qh_pos_l = qh_idx_l % blocklen;
                    let qh_offset_l = qh_chunk_l * (blocklen * ncols) + j * blocklen + qh_pos_l;
                    let hi_2_l = ((qh[qh_offset_l] >> qh_shift_l) & 0x3) as i32;
                    let qh_idx_h = qh_half_h + ((base_h + i) % 32);
                    let qh_chunk_h = qh_idx_h / blocklen;
                    let qh_pos_h = qh_idx_h % blocklen;
                    let qh_offset_h = qh_chunk_h * (blocklen * ncols) + j * blocklen + qh_pos_h;
                    let hi_2_h = ((qh[qh_offset_h] >> qh_shift_h) & 0x3) as i32;
                    q_l[i] = ((hi_2_l << 4) | l_4) - 32;
                    q_h[i] = ((hi_2_h << 4) | hi_4) - 32;
                }
                for (a, act) in acts.iter().enumerate() {
                    let da = act.d[l];
                    let q8 = &act.q[l * Q6_K_BLOCK_ELEMS..(l + 1) * Q6_K_BLOCK_ELEMS];
                    let mut sumi_l = 0i32;
                    let mut sumi_h = 0i32;
                    for i in 0..blocklen {
                        sumi_l += q_l[i] * (q8[base_l + i] as i32);
                        sumi_h += q_h[i] * (q8[base_h + i] as i32);
                    }
                    out[j * na + a] += (sumi_l * scale_l + sumi_h * scale_h) as f32 * d_f[j] * da;
                }
            }
        }
    }
}

/// Whether [`gemm_q6_kx8_group_x4`] is the fast Q6_K batch path on this CPU:
/// ARM i8mm with the interleave-8 layout (`ggml_gemm_q6_K_8x8_q8_K`). The
/// scalar Kx8 GEMM measured slower than the per-row NEON dot on ARM, so
/// batch callers should use the Kx8 layout only when this returns true.
#[inline]
pub fn q6_kx8_gemm_uses_acts_x4(interleave: usize) -> bool {
    #[cfg(target_arch = "aarch64")]
    {
        interleave == 8 && std::arch::is_aarch64_feature_detected!("i8mm")
    }
    #[cfg(not(target_arch = "aarch64"))]
    {
        let _ = interleave;
        false
    }
}

/// [`gemm_q6_kx8_group`] against a pre-interleaved activation quad; the
/// Q6_K counterpart of [`gemm_q4_kx8_group_x4`], with the same contract:
/// interleave-8 packing only, quad prepared once per matmul by
/// [`prepare_q8_k_acts_x4`] (up to 4 activations, not [`Q6_KX8_GEMM_NC`]),
/// `out[r * tile.na + a]`.
pub fn gemm_q6_kx8_group_x4(
    packed: &[u8],
    group: usize,
    tile: &Q8KActsX4,
    n_cols: usize,
    interleave: usize,
    out: &mut [f32],
) {
    assert_eq!(
        interleave, 8,
        "the x4 GEMM only exists for interleave-8 packing"
    );
    assert_eq!(out.len(), Q6_KX8_NROWS * tile.na);
    assert!(n_cols.is_multiple_of(Q6_K_BLOCK_ELEMS));
    debug_assert_eq!(tile.n_blocks, n_cols / Q6_K_BLOCK_ELEMS);
    if tile.na == 0 {
        return;
    }
    let nb = n_cols / Q6_K_BLOCK_ELEMS;
    let off = group * nb * Q6_KX8_BLOCK_BYTES;
    let slice = &packed[off..off + nb * Q6_KX8_BLOCK_BYTES];

    #[cfg(target_arch = "aarch64")]
    if std::arch::is_aarch64_feature_detected!("i8mm") {
        unsafe {
            neon::gemm_q6_kx8_q8_k_neon_i8mm(slice, tile, n_cols, out);
        }
        return;
    }
    gemm_q6_kx8_acts_x4_scalar_8(slice, tile, n_cols, out);
}

/// Portable reference for the Q6_K ×4 GEMM: the same math as
/// [`gemv_q6_kx8_q8_k_scalar`] at blocklen 8, per quad row, reading qs and
/// d out of the pre-interleaved [`Q8KActsX4`] (Q6_K has no mins, so the
/// folded bsums are unused). Bit-identical to running that GEMV per
/// activation, which is what the tests assert.
fn gemm_q6_kx8_acts_x4_scalar_8(packed: &[u8], tile: &Q8KActsX4, n_cols: usize, out: &mut [f32]) {
    let nb = n_cols / Q6_K_BLOCK_ELEMS;
    let blocklen = 8;
    let ncols = Q6_KX8_NROWS;
    let blocks_per_half = 64 / blocklen;
    let na = tile.na;
    let mut sumf = [[0f32; Q6_KX8_NROWS]; Q8K_ACTS_X4_NC];
    for l in 0..nb {
        let blk = &packed[l * Q6_KX8_BLOCK_BYTES..][..Q6_KX8_BLOCK_BYTES];
        let d = &blk[0..16];
        let scales = &blk[16..144];
        let ql = &blk[144..1168];
        let qh = &blk[1168..];
        let q8 = &tile.qs[l * Q6_K_BLOCK_ELEMS * 4..][..Q6_K_BLOCK_ELEMS * 4];
        for a in 0..na {
            let da = tile.d[l * 4 + a];
            for k in 0..(Q6_K_BLOCK_ELEMS / (2 * blocklen)) {
                let base_l = (k / blocks_per_half) * 128 + (k % blocks_per_half) * blocklen;
                let base_h = base_l + 64;
                let scale_idx_l = base_l / 16;
                let scale_idx_h = base_h / 16;
                let qh_shift_l = ((base_l % 128) / 32) * 2;
                let qh_shift_h = ((base_h % 128) / 32) * 2;
                let qh_half_l = (base_l / 128) * 32;
                let qh_half_h = (base_h / 128) * 32;
                for j in 0..ncols {
                    let scale_l = scales[scale_idx_l * ncols + j] as i8 as i32;
                    let scale_h = scales[scale_idx_h * ncols + j] as i8 as i32;
                    let mut sumi_l = 0i32;
                    let mut sumi_h = 0i32;
                    for i in 0..blocklen {
                        let ql_pos = k * ncols * blocklen + j * blocklen + i;
                        let l_4 = (ql[ql_pos] & 0x0F) as i32;
                        let hi_4 = ((ql[ql_pos] >> 4) & 0x0F) as i32;
                        let qh_idx_l = qh_half_l + ((base_l + i) % 32);
                        let qh_chunk_l = qh_idx_l / blocklen;
                        let qh_pos_l = qh_idx_l % blocklen;
                        let qh_offset_l = qh_chunk_l * (blocklen * ncols) + j * blocklen + qh_pos_l;
                        let hi_2_l = ((qh[qh_offset_l] >> qh_shift_l) & 0x3) as i32;
                        let qh_idx_h = qh_half_h + ((base_h + i) % 32);
                        let qh_chunk_h = qh_idx_h / blocklen;
                        let qh_pos_h = qh_idx_h % blocklen;
                        let qh_offset_h = qh_chunk_h * (blocklen * ncols) + j * blocklen + qh_pos_h;
                        let hi_2_h = ((qh[qh_offset_h] >> qh_shift_h) & 0x3) as i32;
                        let q_l = ((hi_2_l << 4) | l_4) - 32;
                        let q_h = ((hi_2_h << 4) | hi_4) - 32;
                        // Canonical q8 element `e` lives at run `e/8`, row
                        // `a`, lane `e%8` of the interleaved block.
                        let e_l = base_l + i;
                        let e_h = base_h + i;
                        sumi_l += q_l * (q8[(e_l / 8) * 32 + a * 8 + (e_l % 8)] as i32);
                        sumi_h += q_h * (q8[(e_h / 8) * 32 + a * 8 + (e_h % 8)] as i32);
                    }
                    sumf[a][j] += (sumi_l * scale_l + sumi_h * scale_h) as f32
                        * f16_from_bytes(&d[j * 2..])
                        * da;
                }
            }
        }
    }
    for j in 0..ncols {
        for (a, row) in sumf.iter().take(na).enumerate() {
            out[j * na + a] = row[j];
        }
    }
}

// ---------------------------------------------------------------------------
// Q4_0 ×4 interleaved GEMV/GEMM (llama.cpp `block_q4_0x4` / `ggml_gemv_q4_0_4x4`)
// ---------------------------------------------------------------------------

/// Bytes per interleaved `block_q4_0x4` (4 × f16 d + 64 qs).
pub const Q4_0X4_BLOCK_BYTES: usize = 72;
/// Number of Q4_0 rows packed into one interleaved block.
pub const Q4_0X4_NROWS: usize = 4;
/// qs interleave width for `ggml_gemv_q4_0_4x4_q8_0` (NEON SDOT). The
/// DotProd-only default; [`q4_0x4_interleave`] picks 8 on i8mm hosts.
pub const Q4_0X4_INTERLEAVE: usize = 4;

/// Preferred qs interleave width: 8 on ARM i8mm (`ggml_gemm_q4_0_4x8_q8_0`
/// via `ggml_repack_get_optimal_repack_type`), 4 on DotProd-only NEON and
/// everywhere else (the scalar fallback handles either).
#[inline]
pub fn q4_0x4_interleave() -> usize {
    #[cfg(target_arch = "aarch64")]
    {
        if std::arch::is_aarch64_feature_detected!("i8mm") {
            return 8;
        }
    }
    Q4_0X4_INTERLEAVE
}

const Q4_0X4_XOR_MASK_U32: u32 = 0x8888_8888;
const Q4_0X4_XOR_MASK_U64: u64 = 0x8888_8888_8888_8888;

/// Pack four canonical Q4_0 blocks (same column-block) into one
/// `block_q4_0x4`. Nibble bytes are XOR-masked during interleave so
/// NEON can unpack without explicit `- 8` bias subtraction.
pub fn make_block_q4_0x4(
    rows: [&[u8]; Q4_0X4_NROWS],
    interleave: usize,
) -> [u8; Q4_0X4_BLOCK_BYTES] {
    debug_assert!(interleave == 4 || interleave == 8);
    for r in &rows {
        debug_assert_eq!(r.len(), Q4_0_BLOCK_BYTES);
    }
    let mut out = [0u8; Q4_0X4_BLOCK_BYTES];
    for (i, row) in rows.iter().enumerate() {
        out[i * 2] = row[0];
        out[i * 2 + 1] = row[1];
    }
    let end = (Q4_0_BLOCK_ELEMS * 2) / interleave;
    let qs_out = &mut out[8..];
    for i in 0..end {
        let src_id = i % Q4_0X4_NROWS;
        let src_offset = (i / Q4_0X4_NROWS) * interleave;
        let dst_offset = i * interleave;
        let src_qs = &rows[src_id][2..18];
        if interleave == 4 {
            let mut elems = u32::from_le_bytes(
                src_qs[src_offset..src_offset + 4]
                    .try_into()
                    .expect("4-byte interleave chunk"),
            );
            elems ^= Q4_0X4_XOR_MASK_U32;
            qs_out[dst_offset..dst_offset + 4].copy_from_slice(&elems.to_le_bytes());
        } else {
            let mut elems = u64::from_le_bytes(
                src_qs[src_offset..src_offset + 8]
                    .try_into()
                    .expect("8-byte interleave chunk"),
            );
            elems ^= Q4_0X4_XOR_MASK_U64;
            qs_out[dst_offset..dst_offset + 8].copy_from_slice(&elems.to_le_bytes());
        }
    }
    out
}

/// Repack a Q4_0 matrix into interleaved `block_q4_0x4` groups. Tail rows
/// (not divisible by 4) are omitted; caller dots them with [`crate::dot_q4_0_q8`].
pub fn pack_q4_0_matrix_x4(data: &[u8], rows: usize, cols: usize, interleave: usize) -> Vec<u8> {
    assert!(cols.is_multiple_of(Q4_0_BLOCK_ELEMS));
    let n_blocks = cols / Q4_0_BLOCK_ELEMS;
    let row_bytes = n_blocks * Q4_0_BLOCK_BYTES;
    assert_eq!(data.len(), rows * row_bytes);
    let n_groups = rows / Q4_0X4_NROWS;
    let mut out = Vec::with_capacity(n_groups * n_blocks * Q4_0X4_BLOCK_BYTES);
    for g in 0..n_groups {
        for b in 0..n_blocks {
            let mut row_refs: [&[u8]; Q4_0X4_NROWS] = [&[]; Q4_0X4_NROWS];
            for (r, slot) in row_refs.iter_mut().enumerate() {
                let base = (g * Q4_0X4_NROWS + r) * row_bytes + b * Q4_0_BLOCK_BYTES;
                *slot = &data[base..base + Q4_0_BLOCK_BYTES];
            }
            out.extend_from_slice(&make_block_q4_0x4(row_refs, interleave));
        }
    }
    out
}

#[inline]
fn q4_0x4_nibble_dot(byte: u8, q8_lo: i32, q8_hi: i32) -> i32 {
    let v0 = ((byte << 4) as i8) as i32;
    let v1 = ((byte & 0xF0) as i8) as i32;
    ((v0 * q8_lo) + (v1 * q8_hi)) >> 4
}

/// Scalar GEMV (`ggml_gemv_q4_0_4x{4,8}_q8_0_generic`); `blocklen` is the
/// interleave the matrix was packed with.
fn gemv_q4_0x4_q8_0_scalar(
    packed: &[u8],
    act: &Q8Activations,
    n_cols: usize,
    n_row_groups: usize,
    blocklen: usize,
    out: &mut [f32],
) {
    let nb = n_cols / Q4_0_BLOCK_ELEMS;
    let ncols = Q4_0X4_NROWS;
    debug_assert_eq!(act.n_blocks(), nb);
    debug_assert_eq!(out.len(), n_row_groups * ncols);
    debug_assert_eq!(packed.len(), n_row_groups * nb * Q4_0X4_BLOCK_BYTES);

    for x in 0..n_row_groups {
        let mut sumf = [0f32; 4];
        let group_off = x * nb * Q4_0X4_BLOCK_BYTES;
        for l in 0..nb {
            let blk = &packed[group_off + l * Q4_0X4_BLOCK_BYTES..][..Q4_0X4_BLOCK_BYTES];
            let da = act.d[l];
            let q8 = &act.q[l * Q4_0_BLOCK_ELEMS..(l + 1) * Q4_0_BLOCK_ELEMS];
            for k in 0..(Q4_0_BLOCK_ELEMS / (2 * blocklen)) {
                for j in 0..ncols {
                    let mut sumi = 0i32;
                    for i in 0..blocklen {
                        let byte = blk[8 + k * ncols * blocklen + j * blocklen + i];
                        sumi += q4_0x4_nibble_dot(
                            byte,
                            q8[k * blocklen + i] as i32,
                            q8[k * blocklen + i + Q4_0_BLOCK_ELEMS / 2] as i32,
                        );
                    }
                    sumf[j] += sumi as f32 * f16_from_bytes(&blk[j * 2..]) * da;
                }
            }
        }
        let base = x * ncols;
        out[base..base + ncols].copy_from_slice(&sumf);
    }
}

/// GEMV: interleaved Q4_0 weights × Q8 activation → `n_row_groups * 4` f32s.
/// `interleave` must match the packing (4: NEON SDOT `4x4`; 8: NEON `4x8`).
pub fn gemv_q4_0x4_q8_0(
    packed: &[u8],
    act: &Q8Activations,
    n_cols: usize,
    n_row_groups: usize,
    interleave: usize,
    out: &mut [f32],
) {
    assert!(n_cols.is_multiple_of(Q4_0_BLOCK_ELEMS));
    assert_eq!(out.len(), n_row_groups * Q4_0X4_NROWS);
    match interleave {
        4 => {
            #[cfg(target_arch = "aarch64")]
            {
                if std::arch::is_aarch64_feature_detected!("dotprod") {
                    unsafe {
                        neon::gemv_q4_0x4_q8_0_neon_sdot(packed, act, n_cols, n_row_groups, out);
                    }
                    return;
                }
            }
            gemv_q4_0x4_q8_0_scalar(packed, act, n_cols, n_row_groups, 4, out);
        }
        8 => {
            #[cfg(target_arch = "aarch64")]
            {
                if std::arch::is_aarch64_feature_detected!("dotprod") {
                    unsafe {
                        neon::gemv_q4_0x4_q8_0_neon_4x8(packed, act, n_cols, n_row_groups, out);
                    }
                    return;
                }
            }
            gemv_q4_0x4_q8_0_scalar(packed, act, n_cols, n_row_groups, 8, out);
        }
        _ => panic!("q4_0x4 interleave must be 4 or 8, got {interleave}"),
    }
}

/// How many activations one [`gemm_q4_0x4_group`] pass keeps in flight.
pub const Q4_0X4_GEMM_NC: usize = 4;

/// GEMM counterpart of [`gemv_q4_0x4_group`]: one row-group (4 rows)
/// against `acts.len()` activations at once. `out` is `[row][act]`:
/// `out[r * acts.len() + j]`.
pub fn gemm_q4_0x4_group(
    packed: &[u8],
    group: usize,
    acts: &[Q8Activations],
    n_cols: usize,
    interleave: usize,
    out: &mut [f32],
) {
    assert_eq!(out.len(), Q4_0X4_NROWS * acts.len());
    assert!(n_cols.is_multiple_of(Q4_0_BLOCK_ELEMS));
    if acts.is_empty() {
        return;
    }
    let nb = n_cols / Q4_0_BLOCK_ELEMS;
    let off = group * nb * Q4_0X4_BLOCK_BYTES;
    let slice = &packed[off..off + nb * Q4_0X4_BLOCK_BYTES];

    #[cfg(target_arch = "aarch64")]
    {
        if interleave == 8 && std::arch::is_aarch64_feature_detected!("i8mm") {
            // Compatibility entry: interleaves the quads here, once per
            // call. Batch callers should prepare them once per matmul and
            // use [`gemm_q4_0x4_group_x4`] instead.
            for (t, chunk) in acts.chunks(Q8K_ACTS_X4_NC).enumerate() {
                let tile = prepare_q8_acts_x4(chunk, n_cols);
                let mut tmp = [0f32; Q4_0X4_NROWS * Q8K_ACTS_X4_NC];
                let n = chunk.len();
                unsafe {
                    neon::gemm_q4_0x4_q8_0_neon_i8mm(
                        slice,
                        &tile,
                        n_cols,
                        &mut tmp[..Q4_0X4_NROWS * n],
                    );
                }
                for r in 0..Q4_0X4_NROWS {
                    for j in 0..n {
                        out[r * acts.len() + t * Q8K_ACTS_X4_NC + j] = tmp[r * n + j];
                    }
                }
            }
            return;
        }
        if interleave == 4 && std::arch::is_aarch64_feature_detected!("dotprod") {
            unsafe {
                neon::gemm_q4_0x4_q8_0_neon_sdot(slice, acts, n_cols, out);
            }
            return;
        }
    }
    let mut tmp = [0f32; Q4_0X4_NROWS];
    for (j, act) in acts.iter().enumerate() {
        gemv_q4_0x4_q8_0(slice, act, n_cols, 1, interleave, &mut tmp);
        for (r, v) in tmp.iter().enumerate() {
            out[r * acts.len() + j] = *v;
        }
    }
}

/// Whether [`gemm_q4_0x4_group_x4`] is the fast Q4_0 batch path on this
/// CPU: ARM i8mm with the interleave-8 layout (`ggml_gemm_q4_0_4x8_q8_0`).
#[inline]
pub fn q4_0x4_gemm_uses_acts_x4(interleave: usize) -> bool {
    #[cfg(target_arch = "aarch64")]
    {
        interleave == 8 && std::arch::is_aarch64_feature_detected!("i8mm")
    }
    #[cfg(not(target_arch = "aarch64"))]
    {
        let _ = interleave;
        false
    }
}

/// [`gemm_q4_0x4_group`] against a pre-interleaved activation quad;
/// interleave-8 packing only, quad prepared once per matmul by
/// [`prepare_q8_acts_x4`]. `out` is `[row][act]`: `out[r * tile.na + a]`.
pub fn gemm_q4_0x4_group_x4(
    packed: &[u8],
    group: usize,
    tile: &Q8ActsX4,
    n_cols: usize,
    interleave: usize,
    out: &mut [f32],
) {
    assert_eq!(
        interleave, 8,
        "the x4 GEMM only exists for interleave-8 packing"
    );
    assert_eq!(out.len(), Q4_0X4_NROWS * tile.na);
    assert!(n_cols.is_multiple_of(Q4_0_BLOCK_ELEMS));
    debug_assert_eq!(tile.n_blocks, n_cols / Q4_0_BLOCK_ELEMS);
    if tile.na == 0 {
        return;
    }
    let nb = n_cols / Q4_0_BLOCK_ELEMS;
    let off = group * nb * Q4_0X4_BLOCK_BYTES;
    let slice = &packed[off..off + nb * Q4_0X4_BLOCK_BYTES];

    #[cfg(target_arch = "aarch64")]
    if std::arch::is_aarch64_feature_detected!("i8mm") {
        unsafe {
            neon::gemm_q4_0x4_q8_0_neon_i8mm(slice, tile, n_cols, out);
        }
        return;
    }
    gemm_q4_0x4_acts_x4_scalar_8(slice, tile, n_cols, out);
}

/// Portable reference for the Q4_0 ×4 GEMM: the same math as
/// [`gemv_q4_0x4_q8_0_scalar`] at blocklen 8, per quad row, reading qs and
/// d out of the pre-interleaved [`Q8ActsX4`]. Bit-identical to running
/// that GEMV per activation, which is what the tests assert.
fn gemm_q4_0x4_acts_x4_scalar_8(packed: &[u8], tile: &Q8ActsX4, n_cols: usize, out: &mut [f32]) {
    let nb = n_cols / Q4_0_BLOCK_ELEMS;
    let blocklen = 8;
    let ncols = Q4_0X4_NROWS;
    let na = tile.na;
    let mut sumf = [[0f32; Q4_0X4_NROWS]; Q8K_ACTS_X4_NC];
    for l in 0..nb {
        let blk = &packed[l * Q4_0X4_BLOCK_BYTES..][..Q4_0X4_BLOCK_BYTES];
        let q8 = &tile.qs[l * Q4_0_BLOCK_ELEMS * 4..][..Q4_0_BLOCK_ELEMS * 4];
        for a in 0..na {
            let da = tile.d[l * 4 + a];
            for k in 0..(Q4_0_BLOCK_ELEMS / (2 * blocklen)) {
                for j in 0..ncols {
                    let mut sumi = 0i32;
                    for i in 0..blocklen {
                        let byte = blk[8 + k * ncols * blocklen + j * blocklen + i];
                        // Canonical q8 element `e` lives at run `e/8`, row
                        // `a`, lane `e%8` of the interleaved block.
                        let e0 = k * blocklen + i;
                        let e1 = e0 + Q4_0_BLOCK_ELEMS / 2;
                        sumi += q4_0x4_nibble_dot(
                            byte,
                            q8[(e0 / 8) * 32 + a * 8 + (e0 % 8)] as i32,
                            q8[(e1 / 8) * 32 + a * 8 + (e1 % 8)] as i32,
                        );
                    }
                    sumf[a][j] += sumi as f32 * f16_from_bytes(&blk[j * 2..]) * da;
                }
            }
        }
    }
    for j in 0..ncols {
        for (a, row) in sumf.iter().take(na).enumerate() {
            out[j * na + a] = row[j];
        }
    }
}

/// One row-group (4 outputs) starting at `group` within a packed Q4_0x4 matrix.
#[inline]
pub fn gemv_q4_0x4_group(
    packed: &[u8],
    group: usize,
    act: &Q8Activations,
    n_cols: usize,
    interleave: usize,
    out4: &mut [f32],
) {
    debug_assert_eq!(out4.len(), Q4_0X4_NROWS);
    let nb = n_cols / Q4_0_BLOCK_ELEMS;
    let off = group * nb * Q4_0X4_BLOCK_BYTES;
    let slice = &packed[off..off + nb * Q4_0X4_BLOCK_BYTES];
    gemv_q4_0x4_q8_0(slice, act, n_cols, 1, interleave, out4);
}

/// One row-group (4 outputs) starting at `group` within a packed Q8_0x4 matrix.
#[inline]
pub fn gemv_q8_0x4_group(
    packed: &[u8],
    group: usize,
    act: &Q8Activations,
    n_cols: usize,
    interleave: usize,
    out4: &mut [f32],
) {
    debug_assert_eq!(out4.len(), Q8_0X4_NROWS);
    let nb = n_cols / Q8_0_BLOCK_ELEMS;
    let off = group * nb * Q8_0X4_BLOCK_BYTES;
    let slice = &packed[off..off + nb * Q8_0X4_BLOCK_BYTES];
    gemv_q8_0x4_q8_0(slice, act, n_cols, 1, interleave, out4);
}

#[cfg(target_arch = "aarch64")]
mod neon {
    use super::*;
    use std::arch::aarch64::*;

    #[target_feature(enable = "neon,i8mm")]
    unsafe fn vmmla_s32(mut acc: int32x4_t, a: int8x16_t, b: int8x16_t) -> int32x4_t {
        std::arch::asm!(
            "smmla {acc:v}.4s, {a:v}.16b, {b:v}.16b",
            acc = inout(vreg) acc,
            a = in(vreg) a,
            b = in(vreg) b,
            options(pure, nomem, nostack),
        );
        acc
    }

    #[target_feature(enable = "neon,dotprod")]
    unsafe fn sdot_lane(mut acc: int32x4_t, a: int8x16_t, b: int8x16_t, lane: u32) -> int32x4_t {
        // sdot Vd.4S, Vn.16B, Vm.4B[lane]
        match lane {
            0 => std::arch::asm!(
                "sdot {acc:v}.4s, {a:v}.16b, {b:v}.4b[0]",
                acc = inout(vreg) acc,
                a = in(vreg) a,
                b = in(vreg) b,
                options(pure, nomem, nostack),
            ),
            1 => std::arch::asm!(
                "sdot {acc:v}.4s, {a:v}.16b, {b:v}.4b[1]",
                acc = inout(vreg) acc,
                a = in(vreg) a,
                b = in(vreg) b,
                options(pure, nomem, nostack),
            ),
            2 => std::arch::asm!(
                "sdot {acc:v}.4s, {a:v}.16b, {b:v}.4b[2]",
                acc = inout(vreg) acc,
                a = in(vreg) a,
                b = in(vreg) b,
                options(pure, nomem, nostack),
            ),
            3 => std::arch::asm!(
                "sdot {acc:v}.4s, {a:v}.16b, {b:v}.4b[3]",
                acc = inout(vreg) acc,
                a = in(vreg) a,
                b = in(vreg) b,
                options(pure, nomem, nostack),
            ),
            _ => unreachable!(),
        }
        acc
    }

    /// `sdot Vd.4S, Vn.16B, Vm.16B` -- the plain (non-lane) signed dot.
    #[target_feature(enable = "neon,dotprod")]
    unsafe fn sdot(mut acc: int32x4_t, a: int8x16_t, b: int8x16_t) -> int32x4_t {
        std::arch::asm!(
            "sdot {acc:v}.4s, {a:v}.16b, {b:v}.16b",
            acc = inout(vreg) acc,
            a = in(vreg) a,
            b = in(vreg) b,
            options(pure, nomem, nostack),
        );
        acc
    }

    /// NEON DotProd GEMV for interleave-4 packed weights (Apple Silicon path).
    #[target_feature(enable = "neon,dotprod")]
    pub unsafe fn gemv_q4_kx8_q8_k_neon_sdot(
        packed: &[u8],
        act: &Q8KActivations,
        n_cols: usize,
        n_row_groups: usize,
        out: &mut [f32],
    ) {
        let nb = n_cols / Q4_K_BLOCK_ELEMS;
        let m4b = vdupq_n_u8(0x0f);

        for x in 0..n_row_groups {
            let mut acc_f32 = [vdupq_n_f32(0.0), vdupq_n_f32(0.0)];
            let group_off = x * nb * Q4_KX8_BLOCK_BYTES;

            for b in 0..nb {
                let blk = packed.as_ptr().add(group_off + b * Q4_KX8_BLOCK_BYTES);
                let mut d_arr = [0f32; 8];
                let mut dmin_arr = [0f32; 8];
                for j in 0..8 {
                    d_arr[j] = f16_from_bytes(std::slice::from_raw_parts(blk.add(j * 2), 2));
                    dmin_arr[j] =
                        f16_from_bytes(std::slice::from_raw_parts(blk.add(16 + j * 2), 2));
                }
                let q8_d = act.d[b];
                let sb_scale_0123 = vmulq_n_f32(vld1q_f32(d_arr.as_ptr()), q8_d);
                let sb_scale_4567 = vmulq_n_f32(vld1q_f32(d_arr.as_ptr().add(4)), q8_d);
                let sb_min_0123 = vmulq_n_f32(vld1q_f32(dmin_arr.as_ptr()), q8_d);
                let sb_min_4567 = vmulq_n_f32(vld1q_f32(dmin_arr.as_ptr().add(4)), q8_d);

                let mut bias_acc = [vdupq_n_s32(0), vdupq_n_s32(0)];
                let q8_base = act.q.as_ptr().add(b * Q4_K_BLOCK_ELEMS);
                let bsums_ptr = act.bsums.as_ptr().add(b * 16);
                // Pairwise-add 16 bsums → 8 (matching llama vpaddq_s16).
                let mut bsums_arr = [0i16; 8];
                for (i, slot) in bsums_arr.iter_mut().enumerate() {
                    *slot = *bsums_ptr.add(2 * i) + *bsums_ptr.add(2 * i + 1);
                }

                let scales_base = blk.add(32);
                let qs_base = blk.add(128);

                for sb in 0..4 {
                    let mut acc_lo = [vdupq_n_s32(0), vdupq_n_s32(0)];
                    let mut acc_hi = [vdupq_n_s32(0), vdupq_n_s32(0)];

                    let mut q4sb_mins = [vdupq_n_s16(0); 2];
                    let mut q4sb_scales = [vdupq_n_s16(0); 2];
                    for i in 0..2 {
                        let mut sc = [0u8; 8];
                        let mut mn = [0u8; 8];
                        let offset = sb * 24 + i * 12;
                        decode_scales_mins(
                            std::slice::from_raw_parts(scales_base.add(offset), 12),
                            &mut sc,
                            &mut mn,
                        );
                        let mut sc_i8 = [0i8; 8];
                        let mut mn_i8 = [0i8; 8];
                        for t in 0..8 {
                            sc_i8[t] = sc[t] as i8;
                            mn_i8[t] = mn[t] as i8;
                        }
                        q4sb_scales[i] = vmovl_s8(vld1_s8(sc_i8.as_ptr()));
                        q4sb_mins[i] = vmovl_s8(vld1_s8(mn_i8.as_ptr()));
                    }

                    let mut q8_qs = [vdupq_n_s8(0); 4];
                    for (i, slot) in q8_qs.iter_mut().enumerate() {
                        *slot = vld1q_s8(q8_base.add(sb * 64 + i * 16));
                    }

                    for c in 0..2 {
                        let mut q4_cols = [vdupq_n_u8(0); 8];
                        for (i, slot) in q4_cols.iter_mut().enumerate() {
                            *slot = vld1q_u8(qs_base.add(sb * Q4_K_BLOCK_ELEMS + i * 32 + 16 * c));
                        }

                        acc_lo[c] = sdot_lane(
                            acc_lo[c],
                            vreinterpretq_s8_u8(vandq_u8(q4_cols[0], m4b)),
                            q8_qs[0],
                            0,
                        );
                        acc_lo[c] = sdot_lane(
                            acc_lo[c],
                            vreinterpretq_s8_u8(vandq_u8(q4_cols[1], m4b)),
                            q8_qs[0],
                            1,
                        );
                        acc_lo[c] = sdot_lane(
                            acc_lo[c],
                            vreinterpretq_s8_u8(vandq_u8(q4_cols[2], m4b)),
                            q8_qs[0],
                            2,
                        );
                        acc_lo[c] = sdot_lane(
                            acc_lo[c],
                            vreinterpretq_s8_u8(vandq_u8(q4_cols[3], m4b)),
                            q8_qs[0],
                            3,
                        );
                        acc_lo[c] = sdot_lane(
                            acc_lo[c],
                            vreinterpretq_s8_u8(vandq_u8(q4_cols[4], m4b)),
                            q8_qs[1],
                            0,
                        );
                        acc_lo[c] = sdot_lane(
                            acc_lo[c],
                            vreinterpretq_s8_u8(vandq_u8(q4_cols[5], m4b)),
                            q8_qs[1],
                            1,
                        );
                        acc_lo[c] = sdot_lane(
                            acc_lo[c],
                            vreinterpretq_s8_u8(vandq_u8(q4_cols[6], m4b)),
                            q8_qs[1],
                            2,
                        );
                        acc_lo[c] = sdot_lane(
                            acc_lo[c],
                            vreinterpretq_s8_u8(vandq_u8(q4_cols[7], m4b)),
                            q8_qs[1],
                            3,
                        );

                        acc_hi[c] = sdot_lane(
                            acc_hi[c],
                            vreinterpretq_s8_u8(vshrq_n_u8(q4_cols[0], 4)),
                            q8_qs[2],
                            0,
                        );
                        acc_hi[c] = sdot_lane(
                            acc_hi[c],
                            vreinterpretq_s8_u8(vshrq_n_u8(q4_cols[1], 4)),
                            q8_qs[2],
                            1,
                        );
                        acc_hi[c] = sdot_lane(
                            acc_hi[c],
                            vreinterpretq_s8_u8(vshrq_n_u8(q4_cols[2], 4)),
                            q8_qs[2],
                            2,
                        );
                        acc_hi[c] = sdot_lane(
                            acc_hi[c],
                            vreinterpretq_s8_u8(vshrq_n_u8(q4_cols[3], 4)),
                            q8_qs[2],
                            3,
                        );
                        acc_hi[c] = sdot_lane(
                            acc_hi[c],
                            vreinterpretq_s8_u8(vshrq_n_u8(q4_cols[4], 4)),
                            q8_qs[3],
                            0,
                        );
                        acc_hi[c] = sdot_lane(
                            acc_hi[c],
                            vreinterpretq_s8_u8(vshrq_n_u8(q4_cols[5], 4)),
                            q8_qs[3],
                            1,
                        );
                        acc_hi[c] = sdot_lane(
                            acc_hi[c],
                            vreinterpretq_s8_u8(vshrq_n_u8(q4_cols[6], 4)),
                            q8_qs[3],
                            2,
                        );
                        acc_hi[c] = sdot_lane(
                            acc_hi[c],
                            vreinterpretq_s8_u8(vshrq_n_u8(q4_cols[7], 4)),
                            q8_qs[3],
                            3,
                        );
                    }

                    let sc_0123_lo = vget_low_s16(q4sb_scales[0]);
                    let sc_0123_hi = vget_low_s16(q4sb_scales[1]);
                    let sumf_0123 = vcvtq_f32_s32(vaddq_s32(
                        vmulq_s32(vmovl_s16(sc_0123_lo), acc_lo[0]),
                        vmulq_s32(vmovl_s16(sc_0123_hi), acc_hi[0]),
                    ));
                    acc_f32[0] = vfmaq_f32(acc_f32[0], sb_scale_0123, sumf_0123);

                    let sc_4567_lo = vget_high_s16(q4sb_scales[0]);
                    let sc_4567_hi = vget_high_s16(q4sb_scales[1]);
                    let sumf_4567 = vcvtq_f32_s32(vaddq_s32(
                        vmulq_s32(vmovl_s16(sc_4567_lo), acc_lo[1]),
                        vmulq_s32(vmovl_s16(sc_4567_hi), acc_hi[1]),
                    ));
                    acc_f32[1] = vfmaq_f32(acc_f32[1], sb_scale_4567, sumf_4567);

                    let bsums_vec_lo = vdup_n_s16(bsums_arr[2 * sb]);
                    let bsums_vec_hi = vdup_n_s16(bsums_arr[2 * sb + 1]);
                    bias_acc[0] = vmlal_s16(bias_acc[0], bsums_vec_lo, vget_low_s16(q4sb_mins[0]));
                    bias_acc[0] = vmlal_s16(bias_acc[0], bsums_vec_hi, vget_low_s16(q4sb_mins[1]));
                    bias_acc[1] = vmlal_s16(bias_acc[1], bsums_vec_lo, vget_high_s16(q4sb_mins[0]));
                    bias_acc[1] = vmlal_s16(bias_acc[1], bsums_vec_hi, vget_high_s16(q4sb_mins[1]));
                }

                acc_f32[0] = vmlsq_f32(acc_f32[0], vcvtq_f32_s32(bias_acc[0]), sb_min_0123);
                acc_f32[1] = vmlsq_f32(acc_f32[1], vcvtq_f32_s32(bias_acc[1]), sb_min_4567);
            }

            let base = x * Q4_KX8_NROWS;
            vst1q_f32(out.as_mut_ptr().add(base), acc_f32[0]);
            vst1q_f32(out.as_mut_ptr().add(base + 4), acc_f32[1]);
        }
    }

    /// NEON DotProd GEMV for interleave-4 `block_q5_Kx8` (llama
    /// `ggml_gemv_q5_K_8x4_q8_K`).
    #[target_feature(enable = "neon,dotprod")]
    pub unsafe fn gemv_q5_kx8_q8_k_neon_sdot(
        packed: &[u8],
        act: &Q8KActivations,
        n_cols: usize,
        n_row_groups: usize,
        out: &mut [f32],
    ) {
        let nb = n_cols / Q5_K_BLOCK_ELEMS;
        let m4b = vdupq_n_u8(0x0f);
        let mone = vdupq_n_u8(1);
        let mtwo = vdupq_n_u8(2);

        for x in 0..n_row_groups {
            let mut acc_f32 = [vdupq_n_f32(0.0), vdupq_n_f32(0.0)];
            let group_off = x * nb * Q5_KX8_BLOCK_BYTES;

            for b in 0..nb {
                let blk = packed.as_ptr().add(group_off + b * Q5_KX8_BLOCK_BYTES);
                let mut d_arr = [0f32; 8];
                let mut dmin_arr = [0f32; 8];
                for j in 0..8 {
                    d_arr[j] = f16_from_bytes(std::slice::from_raw_parts(blk.add(j * 2), 2));
                    dmin_arr[j] =
                        f16_from_bytes(std::slice::from_raw_parts(blk.add(16 + j * 2), 2));
                }
                let q8_d = act.d[b];
                let sb_scale_0123 = vmulq_n_f32(vld1q_f32(d_arr.as_ptr()), q8_d);
                let sb_scale_4567 = vmulq_n_f32(vld1q_f32(d_arr.as_ptr().add(4)), q8_d);
                let sb_min_0123 = vmulq_n_f32(vld1q_f32(dmin_arr.as_ptr()), q8_d);
                let sb_min_4567 = vmulq_n_f32(vld1q_f32(dmin_arr.as_ptr().add(4)), q8_d);

                let mut bias_acc = [vdupq_n_s32(0), vdupq_n_s32(0)];
                let q8_base = act.q.as_ptr().add(b * Q5_K_BLOCK_ELEMS);
                let bsums_ptr = act.bsums.as_ptr().add(b * 16);
                let mut bsums_arr = [0i16; 8];
                for (i, slot) in bsums_arr.iter_mut().enumerate() {
                    *slot = *bsums_ptr.add(2 * i) + *bsums_ptr.add(2 * i + 1);
                }

                let scales_base = blk.add(32);
                let qh_base = blk.add(128);
                let qs_base = blk.add(384);

                // qh[c][i]: 2 col-groups × 8 vectors; shift down 2 bits each sb.
                let mut qh = [[vdupq_n_u8(0); 8]; 2];
                for (c, qh_c) in qh.iter_mut().enumerate() {
                    for (i, slot) in qh_c.iter_mut().enumerate() {
                        *slot = vld1q_u8(qh_base.add(i * 32 + 16 * c));
                    }
                }

                for sb in 0..4 {
                    let mut acc_lo = [vdupq_n_s32(0), vdupq_n_s32(0)];
                    let mut acc_hi = [vdupq_n_s32(0), vdupq_n_s32(0)];

                    let mut q5sb_mins = [vdupq_n_s16(0); 2];
                    let mut q5sb_scales = [vdupq_n_s16(0); 2];
                    for i in 0..2 {
                        let mut sc = [0u8; 8];
                        let mut mn = [0u8; 8];
                        let offset = sb * 24 + i * 12;
                        decode_scales_mins(
                            std::slice::from_raw_parts(scales_base.add(offset), 12),
                            &mut sc,
                            &mut mn,
                        );
                        let mut sc_i8 = [0i8; 8];
                        let mut mn_i8 = [0i8; 8];
                        for t in 0..8 {
                            sc_i8[t] = sc[t] as i8;
                            mn_i8[t] = mn[t] as i8;
                        }
                        q5sb_scales[i] = vmovl_s8(vld1_s8(sc_i8.as_ptr()));
                        q5sb_mins[i] = vmovl_s8(vld1_s8(mn_i8.as_ptr()));
                    }

                    let mut q8_qs = [vdupq_n_s8(0); 4];
                    for (i, slot) in q8_qs.iter_mut().enumerate() {
                        *slot = vld1q_s8(q8_base.add(sb * 64 + i * 16));
                    }

                    for c in 0..2 {
                        let mut q5_lo = [vdupq_n_s8(0); 8];
                        let mut q5_hi = [vdupq_n_s8(0); 8];
                        for i in 0..8 {
                            let q5_cols =
                                vld1q_u8(qs_base.add(sb * Q5_K_BLOCK_ELEMS + i * 32 + 16 * c));
                            let hbit_lo = vandq_u8(qh[c][i], mone);
                            let hbit_hi = vshlq_n_u8(vandq_u8(qh[c][i], mtwo), 3);
                            qh[c][i] = vshrq_n_u8(qh[c][i], 2);
                            q5_lo[i] =
                                vreinterpretq_s8_u8(vsliq_n_u8(vandq_u8(q5_cols, m4b), hbit_lo, 4));
                            q5_hi[i] =
                                vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q5_cols, 4), hbit_hi));
                        }
                        acc_lo[c] = sdot_lane(acc_lo[c], q5_lo[0], q8_qs[0], 0);
                        acc_lo[c] = sdot_lane(acc_lo[c], q5_lo[1], q8_qs[0], 1);
                        acc_lo[c] = sdot_lane(acc_lo[c], q5_lo[2], q8_qs[0], 2);
                        acc_lo[c] = sdot_lane(acc_lo[c], q5_lo[3], q8_qs[0], 3);
                        acc_lo[c] = sdot_lane(acc_lo[c], q5_lo[4], q8_qs[1], 0);
                        acc_lo[c] = sdot_lane(acc_lo[c], q5_lo[5], q8_qs[1], 1);
                        acc_lo[c] = sdot_lane(acc_lo[c], q5_lo[6], q8_qs[1], 2);
                        acc_lo[c] = sdot_lane(acc_lo[c], q5_lo[7], q8_qs[1], 3);
                        acc_hi[c] = sdot_lane(acc_hi[c], q5_hi[0], q8_qs[2], 0);
                        acc_hi[c] = sdot_lane(acc_hi[c], q5_hi[1], q8_qs[2], 1);
                        acc_hi[c] = sdot_lane(acc_hi[c], q5_hi[2], q8_qs[2], 2);
                        acc_hi[c] = sdot_lane(acc_hi[c], q5_hi[3], q8_qs[2], 3);
                        acc_hi[c] = sdot_lane(acc_hi[c], q5_hi[4], q8_qs[3], 0);
                        acc_hi[c] = sdot_lane(acc_hi[c], q5_hi[5], q8_qs[3], 1);
                        acc_hi[c] = sdot_lane(acc_hi[c], q5_hi[6], q8_qs[3], 2);
                        acc_hi[c] = sdot_lane(acc_hi[c], q5_hi[7], q8_qs[3], 3);
                    }

                    let sc_0123_lo = vget_low_s16(q5sb_scales[0]);
                    let sc_0123_hi = vget_low_s16(q5sb_scales[1]);
                    let sumf_0123 = vcvtq_f32_s32(vaddq_s32(
                        vmulq_s32(vmovl_s16(sc_0123_lo), acc_lo[0]),
                        vmulq_s32(vmovl_s16(sc_0123_hi), acc_hi[0]),
                    ));
                    acc_f32[0] = vfmaq_f32(acc_f32[0], sb_scale_0123, sumf_0123);

                    let sc_4567_lo = vget_high_s16(q5sb_scales[0]);
                    let sc_4567_hi = vget_high_s16(q5sb_scales[1]);
                    let sumf_4567 = vcvtq_f32_s32(vaddq_s32(
                        vmulq_s32(vmovl_s16(sc_4567_lo), acc_lo[1]),
                        vmulq_s32(vmovl_s16(sc_4567_hi), acc_hi[1]),
                    ));
                    acc_f32[1] = vfmaq_f32(acc_f32[1], sb_scale_4567, sumf_4567);

                    let bsums_vec_lo = vdup_n_s16(bsums_arr[2 * sb]);
                    let bsums_vec_hi = vdup_n_s16(bsums_arr[2 * sb + 1]);
                    bias_acc[0] = vmlal_s16(bias_acc[0], bsums_vec_lo, vget_low_s16(q5sb_mins[0]));
                    bias_acc[0] = vmlal_s16(bias_acc[0], bsums_vec_hi, vget_low_s16(q5sb_mins[1]));
                    bias_acc[1] = vmlal_s16(bias_acc[1], bsums_vec_lo, vget_high_s16(q5sb_mins[0]));
                    bias_acc[1] = vmlal_s16(bias_acc[1], bsums_vec_hi, vget_high_s16(q5sb_mins[1]));
                }

                acc_f32[0] = vmlsq_f32(acc_f32[0], vcvtq_f32_s32(bias_acc[0]), sb_min_0123);
                acc_f32[1] = vmlsq_f32(acc_f32[1], vcvtq_f32_s32(bias_acc[1]), sb_min_4567);
            }

            let base = x * Q5_KX8_NROWS;
            vst1q_f32(out.as_mut_ptr().add(base), acc_f32[0]);
            vst1q_f32(out.as_mut_ptr().add(base + 4), acc_f32[1]);
        }
    }

    /// NEON DotProd GEMV for interleave-8 packed Q4_K weights (llama.cpp
    /// `ggml_gemv_q4_K_8x8_q8_K` in `arch/arm/repack.cpp`). Each 8-byte q8
    /// run is broadcast to both vector halves so one `sdot` covers two
    /// interleaved columns at once.
    #[target_feature(enable = "neon,dotprod")]
    pub unsafe fn gemv_q4_kx8_q8_k_neon_8x8(
        packed: &[u8],
        act: &Q8KActivations,
        n_cols: usize,
        n_row_groups: usize,
        out: &mut [f32],
    ) {
        let nb = n_cols / Q4_K_BLOCK_ELEMS;
        let m4b = vdupq_n_u8(0x0f);

        for x in 0..n_row_groups {
            let mut acc_f32 = [vdupq_n_f32(0.0), vdupq_n_f32(0.0)];
            let group_off = x * nb * Q4_KX8_BLOCK_BYTES;

            for b in 0..nb {
                let blk = packed.as_ptr().add(group_off + b * Q4_KX8_BLOCK_BYTES);
                let mut d_arr = [0f32; 8];
                let mut dmin_arr = [0f32; 8];
                for j in 0..8 {
                    d_arr[j] = f16_from_bytes(std::slice::from_raw_parts(blk.add(j * 2), 2));
                    dmin_arr[j] =
                        f16_from_bytes(std::slice::from_raw_parts(blk.add(16 + j * 2), 2));
                }
                let q8_d = act.d[b];
                let sb_scale = [
                    vmulq_n_f32(vld1q_f32(d_arr.as_ptr()), q8_d),
                    vmulq_n_f32(vld1q_f32(d_arr.as_ptr().add(4)), q8_d),
                ];
                let sb_min = [
                    vmulq_n_f32(vld1q_f32(dmin_arr.as_ptr()), q8_d),
                    vmulq_n_f32(vld1q_f32(dmin_arr.as_ptr().add(4)), q8_d),
                ];

                let q8_base = act.q.as_ptr().add(b * Q4_K_BLOCK_ELEMS);
                let bsums_ptr = act.bsums.as_ptr().add(b * 16);
                let mut bsums_arr = [0i16; 8];
                for (i, slot) in bsums_arr.iter_mut().enumerate() {
                    *slot = *bsums_ptr.add(2 * i) + *bsums_ptr.add(2 * i + 1);
                }

                let scales_base = blk.add(32);
                let qs_base = blk.add(128);

                let mut bias_acc = [vdupq_n_s32(0), vdupq_n_s32(0)];

                for sb in 0..4 {
                    let mut acc_lo = [vdupq_n_s32(0); 4];
                    let mut acc_hi = [vdupq_n_s32(0); 4];

                    let mut q4sb_scales = [vdupq_n_s16(0); 2];
                    let mut q4sb_mins = [vdupq_n_s16(0); 2];
                    for i in 0..2 {
                        let mut sc = [0u8; 8];
                        let mut mn = [0u8; 8];
                        let offset = sb * 24 + i * 12;
                        decode_scales_mins(
                            std::slice::from_raw_parts(scales_base.add(offset), 12),
                            &mut sc,
                            &mut mn,
                        );
                        let mut sc_i8 = [0i8; 8];
                        let mut mn_i8 = [0i8; 8];
                        for t in 0..8 {
                            sc_i8[t] = sc[t] as i8;
                            mn_i8[t] = mn[t] as i8;
                        }
                        q4sb_scales[i] = vmovl_s8(vld1_s8(sc_i8.as_ptr()));
                        q4sb_mins[i] = vmovl_s8(vld1_s8(mn_i8.as_ptr()));
                    }

                    let q8_sb = q8_base.add(sb * 64);
                    let mut q8_qs = [vdupq_n_s8(0); 8];
                    for (i, slot) in q8_qs.iter_mut().enumerate() {
                        *slot = vreinterpretq_s8_s64(vld1q_dup_s64(q8_sb.add(i * 8) as *const i64));
                    }

                    for cp in 0..4 {
                        let q4_qs = [
                            vld1q_u8(qs_base.add(sb * Q4_K_BLOCK_ELEMS + 16 * cp)),
                            vld1q_u8(qs_base.add(sb * Q4_K_BLOCK_ELEMS + 16 * cp + 64)),
                            vld1q_u8(qs_base.add(sb * Q4_K_BLOCK_ELEMS + 16 * cp + 128)),
                            vld1q_u8(qs_base.add(sb * Q4_K_BLOCK_ELEMS + 16 * cp + 192)),
                        ];
                        for m in 0..4 {
                            let q4_lo = vreinterpretq_s8_u8(vandq_u8(q4_qs[m], m4b));
                            let q4_hi = vreinterpretq_s8_u8(vshrq_n_u8(q4_qs[m], 4));
                            acc_lo[cp] = sdot(acc_lo[cp], q4_lo, q8_qs[m]);
                            acc_hi[cp] = sdot(acc_hi[cp], q4_hi, q8_qs[m + 4]);
                        }
                    }

                    for i in 0..2 {
                        let p = i * 2;
                        let (scales_lo, scales_hi) = if i == 0 {
                            (vget_low_s16(q4sb_scales[0]), vget_low_s16(q4sb_scales[1]))
                        } else {
                            (vget_high_s16(q4sb_scales[0]), vget_high_s16(q4sb_scales[1]))
                        };
                        let sumf_0 = vcvtq_f32_s32(vmulq_s32(
                            vmovl_s16(scales_lo),
                            vpaddq_s32(acc_lo[p], acc_lo[p + 1]),
                        ));
                        acc_f32[i] = vfmaq_f32(acc_f32[i], sb_scale[i], sumf_0);
                        let sumf_1 = vcvtq_f32_s32(vmulq_s32(
                            vmovl_s16(scales_hi),
                            vpaddq_s32(acc_hi[p], acc_hi[p + 1]),
                        ));
                        acc_f32[i] = vfmaq_f32(acc_f32[i], sb_scale[i], sumf_1);
                    }

                    let bsums_vec_lo = vdup_n_s16(bsums_arr[2 * sb]);
                    let bsums_vec_hi = vdup_n_s16(bsums_arr[2 * sb + 1]);
                    bias_acc[0] = vmlal_s16(bias_acc[0], bsums_vec_lo, vget_low_s16(q4sb_mins[0]));
                    bias_acc[0] = vmlal_s16(bias_acc[0], bsums_vec_hi, vget_low_s16(q4sb_mins[1]));
                    bias_acc[1] = vmlal_s16(bias_acc[1], bsums_vec_lo, vget_high_s16(q4sb_mins[0]));
                    bias_acc[1] = vmlal_s16(bias_acc[1], bsums_vec_hi, vget_high_s16(q4sb_mins[1]));
                }

                acc_f32[0] = vmlsq_f32(acc_f32[0], vcvtq_f32_s32(bias_acc[0]), sb_min[0]);
                acc_f32[1] = vmlsq_f32(acc_f32[1], vcvtq_f32_s32(bias_acc[1]), sb_min[1]);
            }

            let base = x * Q4_KX8_NROWS;
            vst1q_f32(out.as_mut_ptr().add(base), acc_f32[0]);
            vst1q_f32(out.as_mut_ptr().add(base + 4), acc_f32[1]);
        }
    }

    /// NEON DotProd GEMV for interleave-8 packed Q5_K weights (llama.cpp
    /// `ggml_gemv_q5_K_8x8_q8_K` in `arch/arm/repack.cpp`). Each 8-byte q8
    /// run is broadcast to both vector halves so one `sdot` covers two
    /// interleaved columns at once.
    #[target_feature(enable = "neon,dotprod")]
    pub unsafe fn gemv_q5_kx8_q8_k_neon_8x8(
        packed: &[u8],
        act: &Q8KActivations,
        n_cols: usize,
        n_row_groups: usize,
        out: &mut [f32],
    ) {
        let nb = n_cols / Q5_K_BLOCK_ELEMS;
        let m4b = vdupq_n_u8(0x0f);
        let mone = vdupq_n_u8(1);
        let mtwo = vdupq_n_u8(2);

        for x in 0..n_row_groups {
            let mut acc_f32 = [vdupq_n_f32(0.0), vdupq_n_f32(0.0)];
            let group_off = x * nb * Q5_KX8_BLOCK_BYTES;

            for b in 0..nb {
                let blk = packed.as_ptr().add(group_off + b * Q5_KX8_BLOCK_BYTES);
                let mut d_arr = [0f32; 8];
                let mut dmin_arr = [0f32; 8];
                for j in 0..8 {
                    d_arr[j] = f16_from_bytes(std::slice::from_raw_parts(blk.add(j * 2), 2));
                    dmin_arr[j] =
                        f16_from_bytes(std::slice::from_raw_parts(blk.add(16 + j * 2), 2));
                }
                let q8_d = act.d[b];
                let sb_scale = [
                    vmulq_n_f32(vld1q_f32(d_arr.as_ptr()), q8_d),
                    vmulq_n_f32(vld1q_f32(d_arr.as_ptr().add(4)), q8_d),
                ];
                let sb_min = [
                    vmulq_n_f32(vld1q_f32(dmin_arr.as_ptr()), q8_d),
                    vmulq_n_f32(vld1q_f32(dmin_arr.as_ptr().add(4)), q8_d),
                ];

                let q8_base = act.q.as_ptr().add(b * Q5_K_BLOCK_ELEMS);
                let bsums_ptr = act.bsums.as_ptr().add(b * 16);
                let mut bsums_arr = [0i16; 8];
                for (i, slot) in bsums_arr.iter_mut().enumerate() {
                    *slot = *bsums_ptr.add(2 * i) + *bsums_ptr.add(2 * i + 1);
                }

                let scales_base = blk.add(32);
                let qh_base = blk.add(128);
                let qs_base = blk.add(384);

                // qh state per column pair; two bits consumed per sub-block.
                let mut qh = [[vdupq_n_u8(0); 4]; 4];
                for (cp, qh_cp) in qh.iter_mut().enumerate() {
                    for (m, slot) in qh_cp.iter_mut().enumerate() {
                        *slot = vld1q_u8(qh_base.add(16 * cp + 64 * m));
                    }
                }

                for sb in 0..4 {
                    let mut acc_lo = [vdupq_n_s32(0); 4];
                    let mut acc_hi = [vdupq_n_s32(0); 4];

                    let mut q5sb_scales = [vdupq_n_s16(0); 2];
                    let mut q5sb_mins = [vdupq_n_s16(0); 2];
                    for i in 0..2 {
                        let mut sc = [0u8; 8];
                        let mut mn = [0u8; 8];
                        let offset = sb * 24 + i * 12;
                        decode_scales_mins(
                            std::slice::from_raw_parts(scales_base.add(offset), 12),
                            &mut sc,
                            &mut mn,
                        );
                        let mut sc_i8 = [0i8; 8];
                        let mut mn_i8 = [0i8; 8];
                        for t in 0..8 {
                            sc_i8[t] = sc[t] as i8;
                            mn_i8[t] = mn[t] as i8;
                        }
                        q5sb_scales[i] = vmovl_s8(vld1_s8(sc_i8.as_ptr()));
                        q5sb_mins[i] = vmovl_s8(vld1_s8(mn_i8.as_ptr()));
                    }

                    let q8_sb = q8_base.add(sb * 64);
                    let mut q8_qs = [vdupq_n_s8(0); 8];
                    for (i, slot) in q8_qs.iter_mut().enumerate() {
                        *slot = vreinterpretq_s8_s64(vld1q_dup_s64(q8_sb.add(i * 8) as *const i64));
                    }

                    for cp in 0..4 {
                        let q5_qs = [
                            vld1q_u8(qs_base.add(sb * Q5_K_BLOCK_ELEMS + 16 * cp)),
                            vld1q_u8(qs_base.add(sb * Q5_K_BLOCK_ELEMS + 16 * cp + 64)),
                            vld1q_u8(qs_base.add(sb * Q5_K_BLOCK_ELEMS + 16 * cp + 128)),
                            vld1q_u8(qs_base.add(sb * Q5_K_BLOCK_ELEMS + 16 * cp + 192)),
                        ];
                        for m in 0..4 {
                            let hbit_lo = vandq_u8(qh[cp][m], mone);
                            let hbit_hi = vshlq_n_u8(vandq_u8(qh[cp][m], mtwo), 3);
                            qh[cp][m] = vshrq_n_u8(qh[cp][m], 2);
                            let q5_lo = vreinterpretq_s8_u8(vsliq_n_u8(
                                vandq_u8(q5_qs[m], m4b),
                                hbit_lo,
                                4,
                            ));
                            let q5_hi =
                                vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q5_qs[m], 4), hbit_hi));
                            acc_lo[cp] = sdot(acc_lo[cp], q5_lo, q8_qs[m]);
                            acc_hi[cp] = sdot(acc_hi[cp], q5_hi, q8_qs[m + 4]);
                        }
                    }

                    let bsums_vec_lo = vdup_n_s16(bsums_arr[2 * sb]);
                    let bsums_vec_hi = vdup_n_s16(bsums_arr[2 * sb + 1]);
                    for i in 0..2 {
                        let p = i * 2;
                        let (scales_lo, scales_hi, mins_lo, mins_hi) = if i == 0 {
                            (
                                vget_low_s16(q5sb_scales[0]),
                                vget_low_s16(q5sb_scales[1]),
                                vget_low_s16(q5sb_mins[0]),
                                vget_low_s16(q5sb_mins[1]),
                            )
                        } else {
                            (
                                vget_high_s16(q5sb_scales[0]),
                                vget_high_s16(q5sb_scales[1]),
                                vget_high_s16(q5sb_mins[0]),
                                vget_high_s16(q5sb_mins[1]),
                            )
                        };
                        let sumf_0 = vcvtq_f32_s32(vmulq_s32(
                            vmovl_s16(scales_lo),
                            vpaddq_s32(acc_lo[p], acc_lo[p + 1]),
                        ));
                        acc_f32[i] = vfmaq_f32(acc_f32[i], sb_scale[i], sumf_0);
                        let sumf_1 = vcvtq_f32_s32(vmulq_s32(
                            vmovl_s16(scales_hi),
                            vpaddq_s32(acc_hi[p], acc_hi[p + 1]),
                        ));
                        acc_f32[i] = vfmaq_f32(acc_f32[i], sb_scale[i], sumf_1);

                        let mut bias = vmull_s16(bsums_vec_lo, mins_lo);
                        bias = vmlal_s16(bias, bsums_vec_hi, mins_hi);
                        acc_f32[i] = vmlsq_f32(acc_f32[i], sb_min[i], vcvtq_f32_s32(bias));
                    }
                }
            }

            let base = x * Q5_KX8_NROWS;
            vst1q_f32(out.as_mut_ptr().add(base), acc_f32[0]);
            vst1q_f32(out.as_mut_ptr().add(base + 4), acc_f32[1]);
        }
    }

    /// NEON DotProd GEMV for interleave-8 packed Q6_K weights (llama.cpp
    /// `ggml_gemv_q6_K_8x8_q8_K` in `arch/arm/repack.cpp`). The -32 offset
    /// is folded into a bsums × scales bias (shifted left 5) instead of
    /// being subtracted from every value.
    #[target_feature(enable = "neon,dotprod")]
    pub unsafe fn gemv_q6_kx8_q8_k_neon_8x8(
        packed: &[u8],
        act: &Q8KActivations,
        n_cols: usize,
        n_row_groups: usize,
        out: &mut [f32],
    ) {
        let nb = n_cols / Q6_K_BLOCK_ELEMS;
        let m4b = vdupq_n_u8(0x0f);
        let mask_lo = vdupq_n_u8(0x03);
        let mask_hi = vdupq_n_u8(0x30);

        for x in 0..n_row_groups {
            let mut acc_f32 = [vdupq_n_f32(0.0), vdupq_n_f32(0.0)];
            let group_off = x * nb * Q6_KX8_BLOCK_BYTES;

            for b in 0..nb {
                let blk = packed.as_ptr().add(group_off + b * Q6_KX8_BLOCK_BYTES);
                let scales_base = blk.add(16) as *const i8;
                let ql_blk = blk.add(144);
                let qh_blk = blk.add(1168);

                let mut d_arr = [0f32; 8];
                for (j, slot) in d_arr.iter_mut().enumerate() {
                    *slot = f16_from_bytes(std::slice::from_raw_parts(blk.add(j * 2), 2));
                }
                let q8_d = act.d[b];
                let sb_scale = [
                    vmulq_n_f32(vld1q_f32(d_arr.as_ptr()), q8_d),
                    vmulq_n_f32(vld1q_f32(d_arr.as_ptr().add(4)), q8_d),
                ];

                let mut acc = [vdup_n_s32(0); 4];

                // 16 groups of 8 i8 scales, widened once per block.
                let mut q6_scales = [0i16; 16 * 8];
                for i in 0..16 {
                    let s16 = vmovl_s8(vld1_s8(scales_base.add(i * 8)));
                    vst1q_s16(q6_scales.as_mut_ptr().add(i * 8), s16);
                }

                // Bias: bsums × scales × 32 replaces subtracting 32 from
                // every 6-bit value.
                let mut bias_lo = vdupq_n_s32(0);
                let mut bias_hi = vdupq_n_s32(0);
                for i in (0..16).step_by(4) {
                    let bsums_vec = vld1_s16(act.bsums.as_ptr().add(b * 16 + i));
                    let sc = q6_scales.as_ptr();
                    bias_lo = vmlal_lane_s16::<0>(bias_lo, vld1_s16(sc.add(i * 8)), bsums_vec);
                    bias_hi = vmlal_lane_s16::<0>(bias_hi, vld1_s16(sc.add(i * 8 + 4)), bsums_vec);
                    bias_lo =
                        vmlal_lane_s16::<1>(bias_lo, vld1_s16(sc.add((i + 1) * 8)), bsums_vec);
                    bias_hi =
                        vmlal_lane_s16::<1>(bias_hi, vld1_s16(sc.add((i + 1) * 8 + 4)), bsums_vec);
                    bias_lo =
                        vmlal_lane_s16::<2>(bias_lo, vld1_s16(sc.add((i + 2) * 8)), bsums_vec);
                    bias_hi =
                        vmlal_lane_s16::<2>(bias_hi, vld1_s16(sc.add((i + 2) * 8 + 4)), bsums_vec);
                    bias_lo =
                        vmlal_lane_s16::<3>(bias_lo, vld1_s16(sc.add((i + 3) * 8)), bsums_vec);
                    bias_hi =
                        vmlal_lane_s16::<3>(bias_hi, vld1_s16(sc.add((i + 3) * 8 + 4)), bsums_vec);
                }
                bias_lo = vshlq_n_s32(bias_lo, 5);
                bias_hi = vshlq_n_s32(bias_hi, 5);

                for half in 0..2 {
                    let ql_base = ql_blk.add(half * 512);
                    let qh_base = qh_blk.add(half * 256);
                    let q8_half = act.q.as_ptr().add(b * Q6_K_BLOCK_ELEMS + half * 128);

                    for sb in 0..4 {
                        let q8_base_l = q8_half.add(sb * 16);
                        let q8_base_h = q8_base_l.add(64);
                        let mut q8_l = [vdupq_n_s8(0); 2];
                        let mut q8_h = [vdupq_n_s8(0); 2];
                        for i in 0..2 {
                            q8_l[i] = vreinterpretq_s8_s64(vld1q_dup_s64(
                                q8_base_l.add(i * 8) as *const i64
                            ));
                            q8_h[i] = vreinterpretq_s8_s64(vld1q_dup_s64(
                                q8_base_h.add(i * 8) as *const i64
                            ));
                        }

                        let ql_off = sb * (Q6_K_BLOCK_ELEMS / 2);
                        let qh_off = ql_off & 255; // wraps after 256 bytes
                        let mut q6_ql_0 = [vdupq_n_u8(0); 4];
                        let mut q6_ql_1 = [vdupq_n_u8(0); 4];
                        let mut q6_qh_0 = [vdupq_n_u8(0); 4];
                        let mut q6_qh_1 = [vdupq_n_u8(0); 4];
                        for k in 0..4 {
                            q6_ql_0[k] = vld1q_u8(ql_base.add(ql_off + 16 * k));
                            q6_ql_1[k] = vld1q_u8(ql_base.add(ql_off + 64 + 16 * k));
                            q6_qh_0[k] = vld1q_u8(qh_base.add(qh_off + 16 * k));
                            q6_qh_1[k] = vld1q_u8(qh_base.add(qh_off + 64 + 16 * k));
                        }
                        // High bits for sub-blocks 2 and 3 sit two bits up.
                        if sb > 1 {
                            for k in 0..4 {
                                q6_qh_0[k] = vshrq_n_u8(q6_qh_0[k], 2);
                                q6_qh_1[k] = vshrq_n_u8(q6_qh_1[k], 2);
                            }
                        }

                        for cp in 0..4 {
                            let hh_0 = vandq_u8(q6_qh_0[cp], mask_hi);
                            let hh_1 = vandq_u8(q6_qh_1[cp], mask_hi);

                            // q6 = low4 | high2<<4; no -32 here, the bias
                            // pass above already carries it.
                            let q6_l0 = vreinterpretq_s8_u8(vsliq_n_u8(
                                vandq_u8(q6_ql_0[cp], m4b),
                                vandq_u8(q6_qh_0[cp], mask_lo),
                                4,
                            ));
                            let q6_l1 = vreinterpretq_s8_u8(vsliq_n_u8(
                                vandq_u8(q6_ql_1[cp], m4b),
                                vandq_u8(q6_qh_1[cp], mask_lo),
                                4,
                            ));
                            let q6_h0 =
                                vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q6_ql_0[cp], 4), hh_0));
                            let q6_h1 =
                                vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q6_ql_1[cp], 4), hh_1));

                            let mut sb_acc_l = vdupq_n_s32(0);
                            sb_acc_l = sdot(sb_acc_l, q6_l0, q8_l[0]);
                            sb_acc_l = sdot(sb_acc_l, q6_l1, q8_l[1]);
                            let mut sb_acc_h = vdupq_n_s32(0);
                            sb_acc_h = sdot(sb_acc_h, q6_h0, q8_h[0]);
                            sb_acc_h = sdot(sb_acc_h, q6_h1, q8_h[1]);

                            let sum_l = vpadd_s32(vget_low_s32(sb_acc_l), vget_high_s32(sb_acc_l));
                            let sum_h = vpadd_s32(vget_low_s32(sb_acc_h), vget_high_s32(sb_acc_h));

                            let scale_idx_l = half * 8 + sb;
                            let scale_idx_h = half * 8 + sb + 4;
                            let scale_vec_l = vset_lane_s32::<1>(
                                i32::from(q6_scales[scale_idx_l * 8 + cp * 2 + 1]),
                                vdup_n_s32(i32::from(q6_scales[scale_idx_l * 8 + cp * 2])),
                            );
                            let scale_vec_h = vset_lane_s32::<1>(
                                i32::from(q6_scales[scale_idx_h * 8 + cp * 2 + 1]),
                                vdup_n_s32(i32::from(q6_scales[scale_idx_h * 8 + cp * 2])),
                            );

                            acc[cp] = vmla_s32(acc[cp], sum_l, scale_vec_l);
                            acc[cp] = vmla_s32(acc[cp], sum_h, scale_vec_h);
                        }
                    }
                }

                acc[0] = vsub_s32(acc[0], vget_low_s32(bias_lo));
                acc[1] = vsub_s32(acc[1], vget_high_s32(bias_lo));
                acc[2] = vsub_s32(acc[2], vget_low_s32(bias_hi));
                acc[3] = vsub_s32(acc[3], vget_high_s32(bias_hi));

                let w_01 = vmul_f32(vcvt_f32_s32(acc[0]), vget_low_f32(sb_scale[0]));
                let w_23 = vmul_f32(vcvt_f32_s32(acc[1]), vget_high_f32(sb_scale[0]));
                let w_45 = vmul_f32(vcvt_f32_s32(acc[2]), vget_low_f32(sb_scale[1]));
                let w_67 = vmul_f32(vcvt_f32_s32(acc[3]), vget_high_f32(sb_scale[1]));

                acc_f32[0] = vaddq_f32(acc_f32[0], vcombine_f32(w_01, w_23));
                acc_f32[1] = vaddq_f32(acc_f32[1], vcombine_f32(w_45, w_67));
            }

            let base = x * Q6_KX8_NROWS;
            vst1q_f32(out.as_mut_ptr().add(base), acc_f32[0]);
            vst1q_f32(out.as_mut_ptr().add(base + 4), acc_f32[1]);
        }
    }

    /// NEON DotProd **GEMM** for interleave-4 packed Q4_K weights: one
    /// row-group (8 rows) against up to [`Q4_KX8_GEMM_NC`] activations.
    ///
    /// Same arithmetic as [`gemv_q4_kx8_q8_k_neon_sdot`], reordered so
    /// the weight-side unpack happens once per activation *tile* rather
    /// than once per activation. Per 256-element super-block that hoists
    /// 16 f16 scale conversions, 8 `decode_scales_mins` calls and 16
    /// `q4_cols` loads out of the batch loop -- which is the whole point,
    /// and the same reason llama.cpp ships `ggml_gemm_q4_K_8x4_q8_K`
    /// beside its GEMV rather than looping the GEMV.
    ///
    /// `out` is `[row][act]`: `out[r * na + j]`.
    #[target_feature(enable = "neon,dotprod")]
    pub unsafe fn gemm_q4_kx8_q8_k_neon_sdot(
        packed: &[u8],
        acts: &[Q8KActivations],
        n_cols: usize,
        out: &mut [f32],
    ) {
        let na = acts.len();
        debug_assert!(na <= Q4_KX8_GEMM_NC);
        let nb = n_cols / Q4_K_BLOCK_ELEMS;
        let m4b = vdupq_n_u8(0x0f);

        // [act][row-half]; row-half 0 is rows 0..3, 1 is rows 4..7.
        let mut acc_f32 = [[vdupq_n_f32(0.0); 2]; Q4_KX8_GEMM_NC];
        let mut bias_acc = [[vdupq_n_s32(0); 2]; Q4_KX8_GEMM_NC];

        for b in 0..nb {
            let blk = packed.as_ptr().add(b * Q4_KX8_BLOCK_BYTES);

            // --- weight-side, once per block (was once per activation) ---
            let mut d_arr = [0f32; 8];
            let mut dmin_arr = [0f32; 8];
            for j in 0..8 {
                d_arr[j] = f16_from_bytes(std::slice::from_raw_parts(blk.add(j * 2), 2));
                dmin_arr[j] = f16_from_bytes(std::slice::from_raw_parts(blk.add(16 + j * 2), 2));
            }
            let d_lo = vld1q_f32(d_arr.as_ptr());
            let d_hi = vld1q_f32(d_arr.as_ptr().add(4));
            let dmin_lo = vld1q_f32(dmin_arr.as_ptr());
            let dmin_hi = vld1q_f32(dmin_arr.as_ptr().add(4));

            // Per-activation scaling of those, plus the pairwise-added
            // bsums this block needs (llama's vpaddq_s16).
            let mut sb_scale = [[vdupq_n_f32(0.0); 2]; Q4_KX8_GEMM_NC];
            let mut sb_min = [[vdupq_n_f32(0.0); 2]; Q4_KX8_GEMM_NC];
            let mut bsums_arr = [[0i16; 8]; Q4_KX8_GEMM_NC];
            for (a, act) in acts.iter().enumerate() {
                let q8_d = act.d[b];
                sb_scale[a] = [vmulq_n_f32(d_lo, q8_d), vmulq_n_f32(d_hi, q8_d)];
                sb_min[a] = [vmulq_n_f32(dmin_lo, q8_d), vmulq_n_f32(dmin_hi, q8_d)];
                let bsums_ptr = act.bsums.as_ptr().add(b * 16);
                for (i, slot) in bsums_arr[a].iter_mut().enumerate() {
                    *slot = *bsums_ptr.add(2 * i) + *bsums_ptr.add(2 * i + 1);
                }
            }

            let scales_base = blk.add(32);
            let qs_base = blk.add(128);

            for sb in 0..4 {
                // 6-bit scale/min decode: once per block-quarter, not
                // once per (block-quarter, activation).
                let mut q4sb_mins = [vdupq_n_s16(0); 2];
                let mut q4sb_scales = [vdupq_n_s16(0); 2];
                for i in 0..2 {
                    let mut sc = [0u8; 8];
                    let mut mn = [0u8; 8];
                    let offset = sb * 24 + i * 12;
                    decode_scales_mins(
                        std::slice::from_raw_parts(scales_base.add(offset), 12),
                        &mut sc,
                        &mut mn,
                    );
                    let mut sc_i8 = [0i8; 8];
                    let mut mn_i8 = [0i8; 8];
                    for t in 0..8 {
                        sc_i8[t] = sc[t] as i8;
                        mn_i8[t] = mn[t] as i8;
                    }
                    q4sb_scales[i] = vmovl_s8(vld1_s8(sc_i8.as_ptr()));
                    q4sb_mins[i] = vmovl_s8(vld1_s8(mn_i8.as_ptr()));
                }

                // `c` selects the row half, so each pass owns one output
                // quad and the accumulators can be consumed immediately
                // instead of all eight staying live.
                for c in 0..2 {
                    let mut q4_cols = [vdupq_n_u8(0); 8];
                    for (i, slot) in q4_cols.iter_mut().enumerate() {
                        *slot = vld1q_u8(qs_base.add(sb * Q4_K_BLOCK_ELEMS + i * 32 + 16 * c));
                    }
                    let (sc_lo, sc_hi) = if c == 0 {
                        (vget_low_s16(q4sb_scales[0]), vget_low_s16(q4sb_scales[1]))
                    } else {
                        (vget_high_s16(q4sb_scales[0]), vget_high_s16(q4sb_scales[1]))
                    };

                    // Mask once per weight tile, not once per
                    // activation, and keep the lane indices literal --
                    // a runtime lane forces a real call per `sdot`
                    // instead of the single instruction it should be.
                    let lo0 = vreinterpretq_s8_u8(vandq_u8(q4_cols[0], m4b));
                    let lo1 = vreinterpretq_s8_u8(vandq_u8(q4_cols[1], m4b));
                    let lo2 = vreinterpretq_s8_u8(vandq_u8(q4_cols[2], m4b));
                    let lo3 = vreinterpretq_s8_u8(vandq_u8(q4_cols[3], m4b));
                    let lo4 = vreinterpretq_s8_u8(vandq_u8(q4_cols[4], m4b));
                    let lo5 = vreinterpretq_s8_u8(vandq_u8(q4_cols[5], m4b));
                    let lo6 = vreinterpretq_s8_u8(vandq_u8(q4_cols[6], m4b));
                    let lo7 = vreinterpretq_s8_u8(vandq_u8(q4_cols[7], m4b));
                    let hi0 = vreinterpretq_s8_u8(vshrq_n_u8(q4_cols[0], 4));
                    let hi1 = vreinterpretq_s8_u8(vshrq_n_u8(q4_cols[1], 4));
                    let hi2 = vreinterpretq_s8_u8(vshrq_n_u8(q4_cols[2], 4));
                    let hi3 = vreinterpretq_s8_u8(vshrq_n_u8(q4_cols[3], 4));
                    let hi4 = vreinterpretq_s8_u8(vshrq_n_u8(q4_cols[4], 4));
                    let hi5 = vreinterpretq_s8_u8(vshrq_n_u8(q4_cols[5], 4));
                    let hi6 = vreinterpretq_s8_u8(vshrq_n_u8(q4_cols[6], 4));
                    let hi7 = vreinterpretq_s8_u8(vshrq_n_u8(q4_cols[7], 4));
                    let sc_lo_w = vmovl_s16(sc_lo);
                    let sc_hi_w = vmovl_s16(sc_hi);

                    for a in 0..na {
                        let q8_base = acts[a].q.as_ptr().add(b * Q4_K_BLOCK_ELEMS);
                        let y0 = vld1q_s8(q8_base.add(sb * 64));
                        let y1 = vld1q_s8(q8_base.add(sb * 64 + 16));
                        let y2 = vld1q_s8(q8_base.add(sb * 64 + 32));
                        let y3 = vld1q_s8(q8_base.add(sb * 64 + 48));
                        let mut acc_lo = vdupq_n_s32(0);
                        let mut acc_hi = vdupq_n_s32(0);
                        acc_lo = sdot_lane(acc_lo, lo0, y0, 0);
                        acc_lo = sdot_lane(acc_lo, lo1, y0, 1);
                        acc_lo = sdot_lane(acc_lo, lo2, y0, 2);
                        acc_lo = sdot_lane(acc_lo, lo3, y0, 3);
                        acc_lo = sdot_lane(acc_lo, lo4, y1, 0);
                        acc_lo = sdot_lane(acc_lo, lo5, y1, 1);
                        acc_lo = sdot_lane(acc_lo, lo6, y1, 2);
                        acc_lo = sdot_lane(acc_lo, lo7, y1, 3);
                        acc_hi = sdot_lane(acc_hi, hi0, y2, 0);
                        acc_hi = sdot_lane(acc_hi, hi1, y2, 1);
                        acc_hi = sdot_lane(acc_hi, hi2, y2, 2);
                        acc_hi = sdot_lane(acc_hi, hi3, y2, 3);
                        acc_hi = sdot_lane(acc_hi, hi4, y3, 0);
                        acc_hi = sdot_lane(acc_hi, hi5, y3, 1);
                        acc_hi = sdot_lane(acc_hi, hi6, y3, 2);
                        acc_hi = sdot_lane(acc_hi, hi7, y3, 3);
                        let sumf = vcvtq_f32_s32(vaddq_s32(
                            vmulq_s32(sc_lo_w, acc_lo),
                            vmulq_s32(sc_hi_w, acc_hi),
                        ));
                        acc_f32[a][c] = vfmaq_f32(acc_f32[a][c], sb_scale[a][c], sumf);
                    }
                }

                for a in 0..na {
                    let bs_lo = vdup_n_s16(bsums_arr[a][2 * sb]);
                    let bs_hi = vdup_n_s16(bsums_arr[a][2 * sb + 1]);
                    bias_acc[a][0] = vmlal_s16(bias_acc[a][0], bs_lo, vget_low_s16(q4sb_mins[0]));
                    bias_acc[a][0] = vmlal_s16(bias_acc[a][0], bs_hi, vget_low_s16(q4sb_mins[1]));
                    bias_acc[a][1] = vmlal_s16(bias_acc[a][1], bs_lo, vget_high_s16(q4sb_mins[0]));
                    bias_acc[a][1] = vmlal_s16(bias_acc[a][1], bs_hi, vget_high_s16(q4sb_mins[1]));
                }
            }

            for a in 0..na {
                for c in 0..2 {
                    acc_f32[a][c] =
                        vmlsq_f32(acc_f32[a][c], vcvtq_f32_s32(bias_acc[a][c]), sb_min[a][c]);
                    bias_acc[a][c] = vdupq_n_s32(0);
                }
            }
        }

        for a in 0..na {
            let mut row = [0f32; Q4_KX8_NROWS];
            vst1q_f32(row.as_mut_ptr(), acc_f32[a][0]);
            vst1q_f32(row.as_mut_ptr().add(4), acc_f32[a][1]);
            for (r, v) in row.iter().enumerate() {
                out[r * na + a] = *v;
            }
        }
    }

    /// NEON DotProd **GEMM** for interleave-4 `block_q5_Kx8` — weight unpack
    /// once per act tile (llama `ggml_gemm_q5_K_8x4_q8_K` motivation).
    #[target_feature(enable = "neon,dotprod")]
    pub unsafe fn gemm_q5_kx8_q8_k_neon_sdot(
        packed: &[u8],
        acts: &[Q8KActivations],
        n_cols: usize,
        out: &mut [f32],
    ) {
        let na = acts.len();
        debug_assert!(na <= Q5_KX8_GEMM_NC);
        let nb = n_cols / Q5_K_BLOCK_ELEMS;
        let m4b = vdupq_n_u8(0x0f);
        let mone = vdupq_n_u8(1);
        let mtwo = vdupq_n_u8(2);

        let mut acc_f32 = [[vdupq_n_f32(0.0); 2]; Q5_KX8_GEMM_NC];
        let mut bias_acc = [[vdupq_n_s32(0); 2]; Q5_KX8_GEMM_NC];

        for b in 0..nb {
            let blk = packed.as_ptr().add(b * Q5_KX8_BLOCK_BYTES);
            let mut d_arr = [0f32; 8];
            let mut dmin_arr = [0f32; 8];
            for j in 0..8 {
                d_arr[j] = f16_from_bytes(std::slice::from_raw_parts(blk.add(j * 2), 2));
                dmin_arr[j] = f16_from_bytes(std::slice::from_raw_parts(blk.add(16 + j * 2), 2));
            }
            let d_lo = vld1q_f32(d_arr.as_ptr());
            let d_hi = vld1q_f32(d_arr.as_ptr().add(4));
            let dmin_lo = vld1q_f32(dmin_arr.as_ptr());
            let dmin_hi = vld1q_f32(dmin_arr.as_ptr().add(4));

            let mut sb_scale = [[vdupq_n_f32(0.0); 2]; Q5_KX8_GEMM_NC];
            let mut sb_min = [[vdupq_n_f32(0.0); 2]; Q5_KX8_GEMM_NC];
            let mut bsums_arr = [[0i16; 8]; Q5_KX8_GEMM_NC];
            for (a, act) in acts.iter().enumerate() {
                let q8_d = act.d[b];
                sb_scale[a] = [vmulq_n_f32(d_lo, q8_d), vmulq_n_f32(d_hi, q8_d)];
                sb_min[a] = [vmulq_n_f32(dmin_lo, q8_d), vmulq_n_f32(dmin_hi, q8_d)];
                let bsums_ptr = act.bsums.as_ptr().add(b * 16);
                for (i, slot) in bsums_arr[a].iter_mut().enumerate() {
                    *slot = *bsums_ptr.add(2 * i) + *bsums_ptr.add(2 * i + 1);
                }
            }

            let scales_base = blk.add(32);
            let qh_base = blk.add(128);
            let qs_base = blk.add(384);

            let mut qh = [[vdupq_n_u8(0); 8]; 2];
            for (c, qh_c) in qh.iter_mut().enumerate() {
                for (i, slot) in qh_c.iter_mut().enumerate() {
                    *slot = vld1q_u8(qh_base.add(i * 32 + 16 * c));
                }
            }

            for sb in 0..4 {
                let mut q5sb_mins = [vdupq_n_s16(0); 2];
                let mut q5sb_scales = [vdupq_n_s16(0); 2];
                for i in 0..2 {
                    let mut sc = [0u8; 8];
                    let mut mn = [0u8; 8];
                    let offset = sb * 24 + i * 12;
                    decode_scales_mins(
                        std::slice::from_raw_parts(scales_base.add(offset), 12),
                        &mut sc,
                        &mut mn,
                    );
                    let mut sc_i8 = [0i8; 8];
                    let mut mn_i8 = [0i8; 8];
                    for t in 0..8 {
                        sc_i8[t] = sc[t] as i8;
                        mn_i8[t] = mn[t] as i8;
                    }
                    q5sb_scales[i] = vmovl_s8(vld1_s8(sc_i8.as_ptr()));
                    q5sb_mins[i] = vmovl_s8(vld1_s8(mn_i8.as_ptr()));
                }

                for c in 0..2 {
                    let mut q5_lo = [vdupq_n_s8(0); 8];
                    let mut q5_hi = [vdupq_n_s8(0); 8];
                    for i in 0..8 {
                        let q5_cols =
                            vld1q_u8(qs_base.add(sb * Q5_K_BLOCK_ELEMS + i * 32 + 16 * c));
                        let hbit_lo = vandq_u8(qh[c][i], mone);
                        let hbit_hi = vshlq_n_u8(vandq_u8(qh[c][i], mtwo), 3);
                        qh[c][i] = vshrq_n_u8(qh[c][i], 2);
                        q5_lo[i] =
                            vreinterpretq_s8_u8(vsliq_n_u8(vandq_u8(q5_cols, m4b), hbit_lo, 4));
                        q5_hi[i] = vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q5_cols, 4), hbit_hi));
                    }
                    let (sc_lo, sc_hi) = if c == 0 {
                        (vget_low_s16(q5sb_scales[0]), vget_low_s16(q5sb_scales[1]))
                    } else {
                        (vget_high_s16(q5sb_scales[0]), vget_high_s16(q5sb_scales[1]))
                    };
                    let sc_lo_w = vmovl_s16(sc_lo);
                    let sc_hi_w = vmovl_s16(sc_hi);

                    for a in 0..na {
                        let q8_base = acts[a].q.as_ptr().add(b * Q5_K_BLOCK_ELEMS);
                        let y0 = vld1q_s8(q8_base.add(sb * 64));
                        let y1 = vld1q_s8(q8_base.add(sb * 64 + 16));
                        let y2 = vld1q_s8(q8_base.add(sb * 64 + 32));
                        let y3 = vld1q_s8(q8_base.add(sb * 64 + 48));
                        let mut acc_lo = vdupq_n_s32(0);
                        let mut acc_hi = vdupq_n_s32(0);
                        acc_lo = sdot_lane(acc_lo, q5_lo[0], y0, 0);
                        acc_lo = sdot_lane(acc_lo, q5_lo[1], y0, 1);
                        acc_lo = sdot_lane(acc_lo, q5_lo[2], y0, 2);
                        acc_lo = sdot_lane(acc_lo, q5_lo[3], y0, 3);
                        acc_lo = sdot_lane(acc_lo, q5_lo[4], y1, 0);
                        acc_lo = sdot_lane(acc_lo, q5_lo[5], y1, 1);
                        acc_lo = sdot_lane(acc_lo, q5_lo[6], y1, 2);
                        acc_lo = sdot_lane(acc_lo, q5_lo[7], y1, 3);
                        acc_hi = sdot_lane(acc_hi, q5_hi[0], y2, 0);
                        acc_hi = sdot_lane(acc_hi, q5_hi[1], y2, 1);
                        acc_hi = sdot_lane(acc_hi, q5_hi[2], y2, 2);
                        acc_hi = sdot_lane(acc_hi, q5_hi[3], y2, 3);
                        acc_hi = sdot_lane(acc_hi, q5_hi[4], y3, 0);
                        acc_hi = sdot_lane(acc_hi, q5_hi[5], y3, 1);
                        acc_hi = sdot_lane(acc_hi, q5_hi[6], y3, 2);
                        acc_hi = sdot_lane(acc_hi, q5_hi[7], y3, 3);
                        let sumf = vcvtq_f32_s32(vaddq_s32(
                            vmulq_s32(sc_lo_w, acc_lo),
                            vmulq_s32(sc_hi_w, acc_hi),
                        ));
                        acc_f32[a][c] = vfmaq_f32(acc_f32[a][c], sb_scale[a][c], sumf);
                    }
                }

                for a in 0..na {
                    let bs_lo = vdup_n_s16(bsums_arr[a][2 * sb]);
                    let bs_hi = vdup_n_s16(bsums_arr[a][2 * sb + 1]);
                    bias_acc[a][0] = vmlal_s16(bias_acc[a][0], bs_lo, vget_low_s16(q5sb_mins[0]));
                    bias_acc[a][0] = vmlal_s16(bias_acc[a][0], bs_hi, vget_low_s16(q5sb_mins[1]));
                    bias_acc[a][1] = vmlal_s16(bias_acc[a][1], bs_lo, vget_high_s16(q5sb_mins[0]));
                    bias_acc[a][1] = vmlal_s16(bias_acc[a][1], bs_hi, vget_high_s16(q5sb_mins[1]));
                }
            }

            for a in 0..na {
                for c in 0..2 {
                    acc_f32[a][c] =
                        vmlsq_f32(acc_f32[a][c], vcvtq_f32_s32(bias_acc[a][c]), sb_min[a][c]);
                    bias_acc[a][c] = vdupq_n_s32(0);
                }
            }
        }

        for a in 0..na {
            let mut row = [0f32; Q5_KX8_NROWS];
            vst1q_f32(row.as_mut_ptr(), acc_f32[a][0]);
            vst1q_f32(row.as_mut_ptr().add(4), acc_f32[a][1]);
            for (r, v) in row.iter().enumerate() {
                out[r * na + a] = *v;
            }
        }
    }

    /// NEON i8mm **GEMM** for interleave-8 packed Q4_K weights (llama.cpp
    /// `ggml_gemm_q4_K_8x8_q8_K` in `arch/arm/repack.cpp`). Uses `vmmlaq_s32`
    /// on 2×8×8 tiles; the activation quad arrives pre-interleaved as
    /// [`Q8KActsX4`] (llama's `block_q8_Kx4` in `wdata`), so nothing here is
    /// repacked per row-group.
    #[target_feature(enable = "neon,i8mm")]
    pub unsafe fn gemm_q4_kx8_q8_k_neon_i8mm(
        packed: &[u8],
        tile: &Q8KActsX4,
        n_cols: usize,
        out: &mut [f32],
    ) {
        let na = tile.na;
        debug_assert!(na <= Q4_KX8_GEMM_NC);
        let nb = n_cols / Q4_K_BLOCK_ELEMS;
        debug_assert_eq!(tile.n_blocks, nb);
        let m4b = vdupq_n_u8(0x0f);
        const Q8_K_BLOCKLEN: usize = 4;

        let mut acc_f32 = [vdupq_n_f32(0.0); Q4_KX8_GEMM_NC * 2];

        for b in 0..nb {
            let blk = packed.as_ptr().add(b * Q4_KX8_BLOCK_BYTES);
            let bsums_base = tile.bsums.as_ptr().add(b * Q8_K_BLOCKLEN * 8);

            let mut acc = [vdupq_n_s32(0); 8];
            let mut bias_acc = [vdupq_n_s32(0); 8];
            for i in 0..8 {
                acc[i] = vdupq_n_s32(0);
                bias_acc[i] = vdupq_n_s32(0);
            }

            let scales_base = blk.add(32);
            let qs_base = blk.add(128);
            let q8_base = tile.qs.as_ptr().add(b * Q4_K_BLOCK_ELEMS * 4);

            for sb in 0..4 {
                let mut q4sb_scales = [[0i8; 8]; 2];
                let mut q4sb_mins = [vdupq_n_s16(0); 2];
                for i in 0..2 {
                    let mut sc = [0u8; 8];
                    let mut mn = [0u8; 8];
                    let offset = sb * 24 + i * 12;
                    decode_scales_mins(
                        std::slice::from_raw_parts(scales_base.add(offset), 12),
                        &mut sc,
                        &mut mn,
                    );
                    let mut mn_i8 = [0i8; 8];
                    for t in 0..8 {
                        q4sb_scales[i][t] = sc[t] as i8;
                        mn_i8[t] = mn[t] as i8;
                    }
                    q4sb_mins[i] = vmovl_s8(vld1_s8(mn_i8.as_ptr()));
                }

                let q8_sb = q8_base.add(sb * 256);
                let mut q8_qs_01 = [vdupq_n_s8(0); 8];
                let mut q8_qs_23 = [vdupq_n_s8(0); 8];
                for i in 0..8 {
                    q8_qs_01[i] = vld1q_s8(q8_sb.add(i * 32));
                    q8_qs_23[i] = vld1q_s8(q8_sb.add(i * 32 + 16));
                }
                let q8s = [q8_qs_01, q8_qs_23];

                for cp in 0..4 {
                    let mut sb_acc = [vdupq_n_s32(0); 4];

                    let q4_qs = [
                        vld1q_u8(qs_base.add(sb * Q4_K_BLOCK_ELEMS + 16 * cp)),
                        vld1q_u8(qs_base.add(sb * Q4_K_BLOCK_ELEMS + 16 * cp + 64)),
                        vld1q_u8(qs_base.add(sb * Q4_K_BLOCK_ELEMS + 16 * cp + 128)),
                        vld1q_u8(qs_base.add(sb * Q4_K_BLOCK_ELEMS + 16 * cp + 192)),
                    ];
                    let q4_nibbles = [
                        [
                            vreinterpretq_s8_u8(vandq_u8(q4_qs[0], m4b)),
                            vreinterpretq_s8_u8(vandq_u8(q4_qs[1], m4b)),
                            vreinterpretq_s8_u8(vandq_u8(q4_qs[2], m4b)),
                            vreinterpretq_s8_u8(vandq_u8(q4_qs[3], m4b)),
                        ],
                        [
                            vreinterpretq_s8_u8(vshrq_n_u8(q4_qs[0], 4)),
                            vreinterpretq_s8_u8(vshrq_n_u8(q4_qs[1], 4)),
                            vreinterpretq_s8_u8(vshrq_n_u8(q4_qs[2], 4)),
                            vreinterpretq_s8_u8(vshrq_n_u8(q4_qs[3], 4)),
                        ],
                    ];

                    for rp in 0..2 {
                        for blk in 0..2 {
                            let q8 = &q8s[rp][4 * blk..4 * blk + 4];
                            let q4 = &q4_nibbles[blk];
                            let mut tile_acc = sb_acc[2 * rp + blk];
                            for qs_offset in 0..4 {
                                tile_acc = vmmla_s32(tile_acc, q4[qs_offset], q8[qs_offset]);
                            }
                            sb_acc[2 * rp + blk] = tile_acc;
                        }
                    }

                    let scale_offset = cp * 2;
                    let block_scale_0 = vcombine_s32(
                        vdup_n_s32(i32::from(q4sb_scales[0][scale_offset])),
                        vdup_n_s32(i32::from(q4sb_scales[0][scale_offset + 1])),
                    );
                    let block_scale_1 = vcombine_s32(
                        vdup_n_s32(i32::from(q4sb_scales[1][scale_offset])),
                        vdup_n_s32(i32::from(q4sb_scales[1][scale_offset + 1])),
                    );

                    acc[cp] = vmlaq_s32(acc[cp], sb_acc[0], block_scale_0);
                    acc[cp + 4] = vmlaq_s32(acc[cp + 4], sb_acc[2], block_scale_0);
                    acc[cp] = vmlaq_s32(acc[cp], sb_acc[1], block_scale_1);
                    acc[cp + 4] = vmlaq_s32(acc[cp + 4], sb_acc[3], block_scale_1);
                }

                for q8_row in 0..Q8_K_BLOCKLEN {
                    let bs_lo = vdup_n_s16(*bsums_base.add(q8_row * 8 + 2 * sb));
                    let bs_hi = vdup_n_s16(*bsums_base.add(q8_row * 8 + 2 * sb + 1));
                    bias_acc[2 * q8_row] =
                        vmlal_s16(bias_acc[2 * q8_row], bs_lo, vget_low_s16(q4sb_mins[0]));
                    bias_acc[2 * q8_row] =
                        vmlal_s16(bias_acc[2 * q8_row], bs_hi, vget_low_s16(q4sb_mins[1]));
                    bias_acc[2 * q8_row + 1] =
                        vmlal_s16(bias_acc[2 * q8_row + 1], bs_lo, vget_high_s16(q4sb_mins[0]));
                    bias_acc[2 * q8_row + 1] =
                        vmlal_s16(bias_acc[2 * q8_row + 1], bs_hi, vget_high_s16(q4sb_mins[1]));
                }
            }

            for lane in acc.iter_mut() {
                let aux = vzip_s32(vget_low_s32(*lane), vget_high_s32(*lane));
                *lane = vcombine_s32(aux.0, aux.1);
            }
            let reorder_acc = [
                vcombine_s32(vget_low_s32(acc[0]), vget_low_s32(acc[1])),
                vcombine_s32(vget_low_s32(acc[2]), vget_low_s32(acc[3])),
                vcombine_s32(vget_high_s32(acc[0]), vget_high_s32(acc[1])),
                vcombine_s32(vget_high_s32(acc[2]), vget_high_s32(acc[3])),
                vcombine_s32(vget_low_s32(acc[4]), vget_low_s32(acc[5])),
                vcombine_s32(vget_low_s32(acc[6]), vget_low_s32(acc[7])),
                vcombine_s32(vget_high_s32(acc[4]), vget_high_s32(acc[5])),
                vcombine_s32(vget_high_s32(acc[6]), vget_high_s32(acc[7])),
            ];

            let mut d_arr = [0f32; 8];
            let mut dmin_arr = [0f32; 8];
            for j in 0..8 {
                d_arr[j] = f16_from_bytes(std::slice::from_raw_parts(blk.add(j * 2), 2));
                dmin_arr[j] = f16_from_bytes(std::slice::from_raw_parts(blk.add(16 + j * 2), 2));
            }

            for i in 0..na {
                for j in 0..2 {
                    let q8_d = vdupq_n_f32(*tile.d.as_ptr().add(b * Q8_K_BLOCKLEN + i));
                    let dmins = vmulq_f32(vld1q_f32(dmin_arr.as_ptr().add(j * 4)), q8_d);
                    let scale = vmulq_f32(vld1q_f32(d_arr.as_ptr().add(j * 4)), q8_d);
                    let idx = 2 * i + j;
                    acc_f32[idx] = vmlsq_f32(acc_f32[idx], vcvtq_f32_s32(bias_acc[idx]), dmins);
                    acc_f32[idx] = vmlaq_f32(acc_f32[idx], vcvtq_f32_s32(reorder_acc[idx]), scale);
                }
            }
        }

        for a in 0..na {
            let mut row = [0f32; Q4_KX8_NROWS];
            vst1q_f32(row.as_mut_ptr(), acc_f32[2 * a]);
            vst1q_f32(row.as_mut_ptr().add(4), acc_f32[2 * a + 1]);
            for (r, v) in row.iter().enumerate() {
                out[r * na + a] = *v;
            }
        }
    }

    /// NEON i8mm **GEMM** for interleave-8 packed Q5_K weights (llama.cpp
    /// `ggml_gemm_q5_K_8x8_q8_K` in `arch/arm/repack.cpp`). Same 2×8×8
    /// `vmmlaq_s32` tiling as [`gemm_q4_kx8_q8_k_neon_i8mm`]; the only
    /// difference is splicing the fifth bit in from `qh` before the MMLAs,
    /// two bits consumed per sub-block.
    #[target_feature(enable = "neon,i8mm")]
    pub unsafe fn gemm_q5_kx8_q8_k_neon_i8mm(
        packed: &[u8],
        tile: &Q8KActsX4,
        n_cols: usize,
        out: &mut [f32],
    ) {
        let na = tile.na;
        debug_assert!(na <= Q5_KX8_GEMM_NC);
        let nb = n_cols / Q5_K_BLOCK_ELEMS;
        debug_assert_eq!(tile.n_blocks, nb);
        let m4b = vdupq_n_u8(0x0f);
        let mone = vdupq_n_u8(1);
        let mtwo = vdupq_n_u8(2);
        const Q8_K_BLOCKLEN: usize = 4;

        let mut acc_f32 = [vdupq_n_f32(0.0); Q5_KX8_GEMM_NC * 2];

        for b in 0..nb {
            let blk = packed.as_ptr().add(b * Q5_KX8_BLOCK_BYTES);
            let bsums_base = tile.bsums.as_ptr().add(b * Q8_K_BLOCKLEN * 8);

            let mut acc = [vdupq_n_s32(0); 8];
            let mut bias_acc = [vdupq_n_s32(0); 8];

            let scales_base = blk.add(32);
            let qh_base = blk.add(128);
            let qs_base = blk.add(384);
            let q8_base = tile.qs.as_ptr().add(b * Q5_K_BLOCK_ELEMS * 4);

            // qh state per column pair; two bits consumed per sub-block.
            let mut qh = [[vdupq_n_u8(0); 4]; 4];
            for (cp, qh_cp) in qh.iter_mut().enumerate() {
                for (m, slot) in qh_cp.iter_mut().enumerate() {
                    *slot = vld1q_u8(qh_base.add(16 * cp + 64 * m));
                }
            }

            for sb in 0..4 {
                let mut q5sb_scales = [[0i8; 8]; 2];
                let mut q5sb_mins = [vdupq_n_s16(0); 2];
                for i in 0..2 {
                    let mut sc = [0u8; 8];
                    let mut mn = [0u8; 8];
                    let offset = sb * 24 + i * 12;
                    decode_scales_mins(
                        std::slice::from_raw_parts(scales_base.add(offset), 12),
                        &mut sc,
                        &mut mn,
                    );
                    let mut mn_i8 = [0i8; 8];
                    for t in 0..8 {
                        q5sb_scales[i][t] = sc[t] as i8;
                        mn_i8[t] = mn[t] as i8;
                    }
                    q5sb_mins[i] = vmovl_s8(vld1_s8(mn_i8.as_ptr()));
                }

                let q8_sb = q8_base.add(sb * 256);
                let mut q8_qs_01 = [vdupq_n_s8(0); 8];
                let mut q8_qs_23 = [vdupq_n_s8(0); 8];
                for i in 0..8 {
                    q8_qs_01[i] = vld1q_s8(q8_sb.add(i * 32));
                    q8_qs_23[i] = vld1q_s8(q8_sb.add(i * 32 + 16));
                }
                let q8s = [q8_qs_01, q8_qs_23];

                for cp in 0..4 {
                    let mut sb_acc = [vdupq_n_s32(0); 4];

                    let q5_qs = [
                        vld1q_u8(qs_base.add(sb * Q5_K_BLOCK_ELEMS + 16 * cp)),
                        vld1q_u8(qs_base.add(sb * Q5_K_BLOCK_ELEMS + 16 * cp + 64)),
                        vld1q_u8(qs_base.add(sb * Q5_K_BLOCK_ELEMS + 16 * cp + 128)),
                        vld1q_u8(qs_base.add(sb * Q5_K_BLOCK_ELEMS + 16 * cp + 192)),
                    ];
                    let mut q5_lo = [vdupq_n_s8(0); 4];
                    let mut q5_hi = [vdupq_n_s8(0); 4];
                    for m in 0..4 {
                        let hbit_lo = vandq_u8(qh[cp][m], mone);
                        let hbit_hi = vshlq_n_u8(vandq_u8(qh[cp][m], mtwo), 3);
                        qh[cp][m] = vshrq_n_u8(qh[cp][m], 2);
                        q5_lo[m] =
                            vreinterpretq_s8_u8(vsliq_n_u8(vandq_u8(q5_qs[m], m4b), hbit_lo, 4));
                        q5_hi[m] = vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q5_qs[m], 4), hbit_hi));
                    }
                    let q5_vals = [q5_lo, q5_hi];

                    for rp in 0..2 {
                        for half in 0..2 {
                            let q8 = &q8s[rp][4 * half..4 * half + 4];
                            let q5 = &q5_vals[half];
                            let mut tile_acc = sb_acc[2 * rp + half];
                            for m in 0..4 {
                                tile_acc = vmmla_s32(tile_acc, q5[m], q8[m]);
                            }
                            sb_acc[2 * rp + half] = tile_acc;
                        }
                    }

                    let scale_offset = cp * 2;
                    let block_scale_0 = vcombine_s32(
                        vdup_n_s32(i32::from(q5sb_scales[0][scale_offset])),
                        vdup_n_s32(i32::from(q5sb_scales[0][scale_offset + 1])),
                    );
                    let block_scale_1 = vcombine_s32(
                        vdup_n_s32(i32::from(q5sb_scales[1][scale_offset])),
                        vdup_n_s32(i32::from(q5sb_scales[1][scale_offset + 1])),
                    );

                    acc[cp] = vmlaq_s32(acc[cp], sb_acc[0], block_scale_0);
                    acc[cp + 4] = vmlaq_s32(acc[cp + 4], sb_acc[2], block_scale_0);
                    acc[cp] = vmlaq_s32(acc[cp], sb_acc[1], block_scale_1);
                    acc[cp + 4] = vmlaq_s32(acc[cp + 4], sb_acc[3], block_scale_1);
                }

                for q8_row in 0..Q8_K_BLOCKLEN {
                    let bs_lo = vdup_n_s16(*bsums_base.add(q8_row * 8 + 2 * sb));
                    let bs_hi = vdup_n_s16(*bsums_base.add(q8_row * 8 + 2 * sb + 1));
                    bias_acc[2 * q8_row] =
                        vmlal_s16(bias_acc[2 * q8_row], bs_lo, vget_low_s16(q5sb_mins[0]));
                    bias_acc[2 * q8_row] =
                        vmlal_s16(bias_acc[2 * q8_row], bs_hi, vget_low_s16(q5sb_mins[1]));
                    bias_acc[2 * q8_row + 1] =
                        vmlal_s16(bias_acc[2 * q8_row + 1], bs_lo, vget_high_s16(q5sb_mins[0]));
                    bias_acc[2 * q8_row + 1] =
                        vmlal_s16(bias_acc[2 * q8_row + 1], bs_hi, vget_high_s16(q5sb_mins[1]));
                }
            }

            for lane in acc.iter_mut() {
                let aux = vzip_s32(vget_low_s32(*lane), vget_high_s32(*lane));
                *lane = vcombine_s32(aux.0, aux.1);
            }
            let reorder_acc = [
                vcombine_s32(vget_low_s32(acc[0]), vget_low_s32(acc[1])),
                vcombine_s32(vget_low_s32(acc[2]), vget_low_s32(acc[3])),
                vcombine_s32(vget_high_s32(acc[0]), vget_high_s32(acc[1])),
                vcombine_s32(vget_high_s32(acc[2]), vget_high_s32(acc[3])),
                vcombine_s32(vget_low_s32(acc[4]), vget_low_s32(acc[5])),
                vcombine_s32(vget_low_s32(acc[6]), vget_low_s32(acc[7])),
                vcombine_s32(vget_high_s32(acc[4]), vget_high_s32(acc[5])),
                vcombine_s32(vget_high_s32(acc[6]), vget_high_s32(acc[7])),
            ];

            let mut d_arr = [0f32; 8];
            let mut dmin_arr = [0f32; 8];
            for j in 0..8 {
                d_arr[j] = f16_from_bytes(std::slice::from_raw_parts(blk.add(j * 2), 2));
                dmin_arr[j] = f16_from_bytes(std::slice::from_raw_parts(blk.add(16 + j * 2), 2));
            }

            for i in 0..na {
                for j in 0..2 {
                    let q8_d = vdupq_n_f32(*tile.d.as_ptr().add(b * Q8_K_BLOCKLEN + i));
                    let dmins = vmulq_f32(vld1q_f32(dmin_arr.as_ptr().add(j * 4)), q8_d);
                    let scale = vmulq_f32(vld1q_f32(d_arr.as_ptr().add(j * 4)), q8_d);
                    let idx = 2 * i + j;
                    acc_f32[idx] = vmlsq_f32(acc_f32[idx], vcvtq_f32_s32(bias_acc[idx]), dmins);
                    acc_f32[idx] = vmlaq_f32(acc_f32[idx], vcvtq_f32_s32(reorder_acc[idx]), scale);
                }
            }
        }

        for a in 0..na {
            let mut row = [0f32; Q5_KX8_NROWS];
            vst1q_f32(row.as_mut_ptr(), acc_f32[2 * a]);
            vst1q_f32(row.as_mut_ptr().add(4), acc_f32[2 * a + 1]);
            for (r, v) in row.iter().enumerate() {
                out[r * na + a] = *v;
            }
        }
    }

    /// NEON i8mm **GEMM** for interleave-8 packed Q6_K weights (llama.cpp
    /// `ggml_gemm_q6_K_8x8_q8_K` in `arch/arm/repack.cpp`). Q6_K has no
    /// mins: the -32 offset is folded into the i8 values before the MMLAs
    /// (63 - 32 fits i8), so there is no bias pass at all.
    #[target_feature(enable = "neon,i8mm")]
    pub unsafe fn gemm_q6_kx8_q8_k_neon_i8mm(
        packed: &[u8],
        tile: &Q8KActsX4,
        n_cols: usize,
        out: &mut [f32],
    ) {
        let na = tile.na;
        debug_assert!(na <= Q8K_ACTS_X4_NC);
        let nb = n_cols / Q6_K_BLOCK_ELEMS;
        debug_assert_eq!(tile.n_blocks, nb);
        let m4b = vdupq_n_u8(0x0f);
        let mask_lo = vdupq_n_u8(0x03);
        let mask_hi = vdupq_n_u8(0x30);
        let m32s = vdupq_n_s8(32);
        const Q8_K_BLOCKLEN: usize = 4;

        let mut acc_f32 = [vdupq_n_f32(0.0); Q8K_ACTS_X4_NC * 2];

        for b in 0..nb {
            let blk = packed.as_ptr().add(b * Q6_KX8_BLOCK_BYTES);
            let scales_base = blk.add(16) as *const i8;
            let ql_blk = blk.add(144);
            let qh_blk = blk.add(1168);
            let q8_blk = tile.qs.as_ptr().add(b * Q6_K_BLOCK_ELEMS * 4);

            let mut acc = [vdupq_n_s32(0); 8];

            // 16 groups of 8 i8 scales, widened once per block.
            let mut q6_scales = [0i16; 16 * 8];
            for i in 0..16 {
                let s16 = vmovl_s8(vld1_s8(scales_base.add(i * 8)));
                vst1q_s16(q6_scales.as_mut_ptr().add(i * 8), s16);
            }

            for half in 0..2 {
                let ql_base = ql_blk.add(half * 512);
                let qh_base = qh_blk.add(half * 256);

                for sb in 0..4 {
                    let q8_base_l = q8_blk.add(half * 512 + sb * 64);
                    let q8_base_h = q8_blk.add(half * 512 + 256 + sb * 64);

                    let mut q8_l_01 = [vdupq_n_s8(0); 2];
                    let mut q8_l_23 = [vdupq_n_s8(0); 2];
                    let mut q8_h_01 = [vdupq_n_s8(0); 2];
                    let mut q8_h_23 = [vdupq_n_s8(0); 2];
                    for i in 0..2 {
                        q8_l_01[i] = vld1q_s8(q8_base_l.add(i * 32));
                        q8_l_23[i] = vld1q_s8(q8_base_l.add(i * 32 + 16));
                        q8_h_01[i] = vld1q_s8(q8_base_h.add(i * 32));
                        q8_h_23[i] = vld1q_s8(q8_base_h.add(i * 32 + 16));
                    }

                    let ql_off = sb * (Q6_K_BLOCK_ELEMS / 2);
                    let qh_off = ql_off & 255; // wraps after 256 bytes
                    let mut q6_ql_0 = [vdupq_n_u8(0); 4];
                    let mut q6_ql_1 = [vdupq_n_u8(0); 4];
                    let mut q6_qh_0 = [vdupq_n_u8(0); 4];
                    let mut q6_qh_1 = [vdupq_n_u8(0); 4];
                    for k in 0..4 {
                        q6_ql_0[k] = vld1q_u8(ql_base.add(ql_off + 16 * k));
                        q6_ql_1[k] = vld1q_u8(ql_base.add(ql_off + 64 + 16 * k));
                        q6_qh_0[k] = vld1q_u8(qh_base.add(qh_off + 16 * k));
                        q6_qh_1[k] = vld1q_u8(qh_base.add(qh_off + 64 + 16 * k));
                    }
                    // High bits for sub-blocks 2 and 3 sit two bits up.
                    if sb > 1 {
                        for k in 0..4 {
                            q6_qh_0[k] = vshrq_n_u8(q6_qh_0[k], 2);
                            q6_qh_1[k] = vshrq_n_u8(q6_qh_1[k], 2);
                        }
                    }

                    for cp in 0..4 {
                        let hh_0 = vandq_u8(q6_qh_0[cp], mask_hi);
                        let hh_1 = vandq_u8(q6_qh_1[cp], mask_hi);

                        // q6 = (low4 | high2<<4) - 32
                        let q6_l0 = vsubq_s8(
                            vreinterpretq_s8_u8(vsliq_n_u8(
                                vandq_u8(q6_ql_0[cp], m4b),
                                vandq_u8(q6_qh_0[cp], mask_lo),
                                4,
                            )),
                            m32s,
                        );
                        let q6_l1 = vsubq_s8(
                            vreinterpretq_s8_u8(vsliq_n_u8(
                                vandq_u8(q6_ql_1[cp], m4b),
                                vandq_u8(q6_qh_1[cp], mask_lo),
                                4,
                            )),
                            m32s,
                        );
                        let q6_h0 = vsubq_s8(
                            vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q6_ql_0[cp], 4), hh_0)),
                            m32s,
                        );
                        let q6_h1 = vsubq_s8(
                            vreinterpretq_s8_u8(vorrq_u8(vshrq_n_u8(q6_ql_1[cp], 4), hh_1)),
                            m32s,
                        );

                        let mut sb_acc_0l = vmmla_s32(vdupq_n_s32(0), q6_l0, q8_l_01[0]);
                        sb_acc_0l = vmmla_s32(sb_acc_0l, q6_l1, q8_l_01[1]);
                        let mut sb_acc_0h = vmmla_s32(vdupq_n_s32(0), q6_h0, q8_h_01[0]);
                        sb_acc_0h = vmmla_s32(sb_acc_0h, q6_h1, q8_h_01[1]);
                        let mut sb_acc_1l = vmmla_s32(vdupq_n_s32(0), q6_l0, q8_l_23[0]);
                        sb_acc_1l = vmmla_s32(sb_acc_1l, q6_l1, q8_l_23[1]);
                        let mut sb_acc_1h = vmmla_s32(vdupq_n_s32(0), q6_h0, q8_h_23[0]);
                        sb_acc_1h = vmmla_s32(sb_acc_1h, q6_h1, q8_h_23[1]);

                        let scale_idx_l = half * 8 + sb;
                        let scale_idx_h = half * 8 + sb + 4;
                        let scale_l = vcombine_s32(
                            vdup_n_s32(i32::from(q6_scales[scale_idx_l * 8 + cp * 2])),
                            vdup_n_s32(i32::from(q6_scales[scale_idx_l * 8 + cp * 2 + 1])),
                        );
                        let scale_h = vcombine_s32(
                            vdup_n_s32(i32::from(q6_scales[scale_idx_h * 8 + cp * 2])),
                            vdup_n_s32(i32::from(q6_scales[scale_idx_h * 8 + cp * 2 + 1])),
                        );

                        acc[cp] = vmlaq_s32(acc[cp], sb_acc_0l, scale_l);
                        acc[cp] = vmlaq_s32(acc[cp], sb_acc_0h, scale_h);
                        acc[cp + 4] = vmlaq_s32(acc[cp + 4], sb_acc_1l, scale_l);
                        acc[cp + 4] = vmlaq_s32(acc[cp + 4], sb_acc_1h, scale_h);
                    }
                }
            }

            for lane in acc.iter_mut() {
                let aux = vzip_s32(vget_low_s32(*lane), vget_high_s32(*lane));
                *lane = vcombine_s32(aux.0, aux.1);
            }
            let reorder_acc = [
                vcombine_s32(vget_low_s32(acc[0]), vget_low_s32(acc[1])),
                vcombine_s32(vget_low_s32(acc[2]), vget_low_s32(acc[3])),
                vcombine_s32(vget_high_s32(acc[0]), vget_high_s32(acc[1])),
                vcombine_s32(vget_high_s32(acc[2]), vget_high_s32(acc[3])),
                vcombine_s32(vget_low_s32(acc[4]), vget_low_s32(acc[5])),
                vcombine_s32(vget_low_s32(acc[6]), vget_low_s32(acc[7])),
                vcombine_s32(vget_high_s32(acc[4]), vget_high_s32(acc[5])),
                vcombine_s32(vget_high_s32(acc[6]), vget_high_s32(acc[7])),
            ];

            let mut d_arr = [0f32; 8];
            for (j, slot) in d_arr.iter_mut().enumerate() {
                *slot = f16_from_bytes(std::slice::from_raw_parts(blk.add(j * 2), 2));
            }

            for i in 0..na {
                for j in 0..2 {
                    let q8_d = vdupq_n_f32(*tile.d.as_ptr().add(b * Q8_K_BLOCKLEN + i));
                    let scale = vmulq_f32(vld1q_f32(d_arr.as_ptr().add(j * 4)), q8_d);
                    let idx = 2 * i + j;
                    acc_f32[idx] = vmlaq_f32(acc_f32[idx], vcvtq_f32_s32(reorder_acc[idx]), scale);
                }
            }
        }

        for a in 0..na {
            let mut row = [0f32; Q6_KX8_NROWS];
            vst1q_f32(row.as_mut_ptr(), acc_f32[2 * a]);
            vst1q_f32(row.as_mut_ptr().add(4), acc_f32[2 * a + 1]);
            for (r, v) in row.iter().enumerate() {
                out[r * na + a] = *v;
            }
        }
    }

    /// NEON DotProd GEMV for `block_q8_0x4` (llama `ggml_gemv_q8_0_4x4_q8_0`).
    #[target_feature(enable = "neon,dotprod")]
    pub unsafe fn gemv_q8_0x4_q8_0_neon_sdot(
        packed: &[u8],
        act: &Q8Activations,
        n_cols: usize,
        n_row_groups: usize,
        out: &mut [f32],
    ) {
        let nb = n_cols / Q8_0_BLOCK_ELEMS;
        for x in 0..n_row_groups {
            let mut acc = vdupq_n_f32(0.0);
            let group_off = x * nb * Q8_0X4_BLOCK_BYTES;
            for b in 0..nb {
                let blk = packed.as_ptr().add(group_off + b * Q8_0X4_BLOCK_BYTES);
                let qs = blk.add(8);
                // Four int8x16: first 64 qs bytes (k=0..3 × 4 rows × 4).
                let b0 = vld1q_s8(qs as *const i8);
                let b1 = vld1q_s8(qs.add(16) as *const i8);
                let b2 = vld1q_s8(qs.add(32) as *const i8);
                let b3 = vld1q_s8(qs.add(48) as *const i8);
                let b4 = vld1q_s8(qs.add(64) as *const i8);
                let b5 = vld1q_s8(qs.add(80) as *const i8);
                let b6 = vld1q_s8(qs.add(96) as *const i8);
                let b7 = vld1q_s8(qs.add(112) as *const i8);

                let a_ptr = act.q.as_ptr().add(b * Q8_0_BLOCK_ELEMS);
                let a0 = vld1q_s8(a_ptr);
                let a1 = vld1q_s8(a_ptr.add(16));

                let mut ret = vdupq_n_s32(0);
                ret = sdot_lane(ret, b0, a0, 0);
                ret = sdot_lane(ret, b1, a0, 1);
                ret = sdot_lane(ret, b2, a0, 2);
                ret = sdot_lane(ret, b3, a0, 3);
                ret = sdot_lane(ret, b4, a1, 0);
                ret = sdot_lane(ret, b5, a1, 1);
                ret = sdot_lane(ret, b6, a1, 2);
                ret = sdot_lane(ret, b7, a1, 3);

                // Four f16 weight scales at blk[0..8] — load as u16 then
                // convert (avoids 4× scalar half::f16 path per block).
                let d_bits = vld1_u16(blk as *const u16);
                let mut dw = [0f32; 4];
                dw[0] = f16::from_bits(vget_lane_u16(d_bits, 0)).to_f32();
                dw[1] = f16::from_bits(vget_lane_u16(d_bits, 1)).to_f32();
                dw[2] = f16::from_bits(vget_lane_u16(d_bits, 2)).to_f32();
                dw[3] = f16::from_bits(vget_lane_u16(d_bits, 3)).to_f32();
                let scale = vmulq_n_f32(vld1q_f32(dw.as_ptr()), act.d[b]);
                acc = vfmaq_f32(acc, vcvtq_f32_s32(ret), scale);
            }
            vst1q_f32(out.as_mut_ptr().add(x * Q8_0X4_NROWS), acc);
        }
    }

    /// NEON DotProd GEMM for one `block_q8_0x4` row-group against
    /// several activations (llama `ggml_gemm_q8_0_4x4_q8_0` in shape).
    ///
    /// The eight weight vectors of a block are loaded once and reused
    /// across a tile of [`Q8_0X4_GEMM_NC`] activations, which is the
    /// whole point of having a GEMM rather than a loop over the GEMV.
    #[target_feature(enable = "neon,dotprod")]
    pub unsafe fn gemm_q8_0x4_q8_0_neon_sdot(
        group: &[u8],
        acts: &[Q8Activations],
        n_cols: usize,
        out: &mut [f32],
    ) {
        let nb = n_cols / Q8_0_BLOCK_ELEMS;
        let n_acts = acts.len();
        let mut j0 = 0;
        while j0 < n_acts {
            let tile = Q8_0X4_GEMM_NC.min(n_acts - j0);
            let mut acc = [vdupq_n_f32(0.0); Q8_0X4_GEMM_NC];
            for b in 0..nb {
                let blk = group.as_ptr().add(b * Q8_0X4_BLOCK_BYTES);
                let qs = blk.add(8);
                let w = [
                    vld1q_s8(qs as *const i8),
                    vld1q_s8(qs.add(16) as *const i8),
                    vld1q_s8(qs.add(32) as *const i8),
                    vld1q_s8(qs.add(48) as *const i8),
                    vld1q_s8(qs.add(64) as *const i8),
                    vld1q_s8(qs.add(80) as *const i8),
                    vld1q_s8(qs.add(96) as *const i8),
                    vld1q_s8(qs.add(112) as *const i8),
                ];
                let d_bits = vld1_u16(blk as *const u16);
                let mut dw = [0f32; 4];
                dw[0] = f16::from_bits(vget_lane_u16(d_bits, 0)).to_f32();
                dw[1] = f16::from_bits(vget_lane_u16(d_bits, 1)).to_f32();
                dw[2] = f16::from_bits(vget_lane_u16(d_bits, 2)).to_f32();
                dw[3] = f16::from_bits(vget_lane_u16(d_bits, 3)).to_f32();
                let dw_v = vld1q_f32(dw.as_ptr());

                for t in 0..tile {
                    let act = &acts[j0 + t];
                    let a_ptr = act.q.as_ptr().add(b * Q8_0_BLOCK_ELEMS);
                    let a0 = vld1q_s8(a_ptr);
                    let a1 = vld1q_s8(a_ptr.add(16));
                    let mut ret = vdupq_n_s32(0);
                    ret = sdot_lane(ret, w[0], a0, 0);
                    ret = sdot_lane(ret, w[1], a0, 1);
                    ret = sdot_lane(ret, w[2], a0, 2);
                    ret = sdot_lane(ret, w[3], a0, 3);
                    ret = sdot_lane(ret, w[4], a1, 0);
                    ret = sdot_lane(ret, w[5], a1, 1);
                    ret = sdot_lane(ret, w[6], a1, 2);
                    ret = sdot_lane(ret, w[7], a1, 3);
                    let scale = vmulq_n_f32(dw_v, act.d[b]);
                    acc[t] = vfmaq_f32(acc[t], vcvtq_f32_s32(ret), scale);
                }
            }
            for t in 0..tile {
                let mut lanes = [0f32; Q8_0X4_NROWS];
                vst1q_f32(lanes.as_mut_ptr(), acc[t]);
                for (r, v) in lanes.iter().enumerate() {
                    out[r * n_acts + j0 + t] = *v;
                }
            }
            j0 += tile;
        }
    }

    /// NEON DotProd GEMV for `block_q4_0x4` (llama `ggml_gemv_q4_0_4x4_q8_0`).
    #[target_feature(enable = "neon,dotprod")]
    pub unsafe fn gemv_q4_0x4_q8_0_neon_sdot(
        packed: &[u8],
        act: &Q8Activations,
        n_cols: usize,
        n_row_groups: usize,
        out: &mut [f32],
    ) {
        let nb = n_cols / Q4_0_BLOCK_ELEMS;
        let maskf0 = vdupq_n_u8(0xF0);
        for x in 0..n_row_groups {
            let mut acc = vdupq_n_f32(0.0);
            let group_off = x * nb * Q4_0X4_BLOCK_BYTES;
            for b in 0..nb {
                let blk = packed.as_ptr().add(group_off + b * Q4_0X4_BLOCK_BYTES);
                let qs = blk.add(8);
                let a_ptr = act.q.as_ptr().add(b * Q4_0_BLOCK_ELEMS);
                let a0 = vld1q_s8(a_ptr);
                let a1 = vld1q_s8(a_ptr.add(16));

                let mut ret = vdupq_n_s32(0);
                for wi in 0..4u32 {
                    let w = vld1q_u8(qs.add(wi as usize * 16));
                    let hi = vreinterpretq_s8_u8(vshlq_n_u8(w, 4));
                    let lo = vreinterpretq_s8_u8(vandq_u8(w, maskf0));
                    ret = sdot_lane(ret, hi, a0, wi);
                    ret = sdot_lane(ret, lo, a1, wi);
                }

                let d_bits = vld1_u16(blk as *const u16);
                let mut dw = [0f32; 4];
                dw[0] = f16::from_bits(vget_lane_u16(d_bits, 0)).to_f32();
                dw[1] = f16::from_bits(vget_lane_u16(d_bits, 1)).to_f32();
                dw[2] = f16::from_bits(vget_lane_u16(d_bits, 2)).to_f32();
                dw[3] = f16::from_bits(vget_lane_u16(d_bits, 3)).to_f32();
                let scale = vmulq_n_f32(vld1q_f32(dw.as_ptr()), act.d[b]);
                acc = vfmaq_f32(acc, vcvtq_f32_s32(vshrq_n_s32(ret, 4)), scale);
            }
            vst1q_f32(out.as_mut_ptr().add(x * Q4_0X4_NROWS), acc);
        }
    }

    /// NEON DotProd GEMM for one `block_q4_0x4` row-group against several
    /// activations (llama `ggml_gemm_q4_0_4x4_q8_0` in shape).
    #[target_feature(enable = "neon,dotprod")]
    pub unsafe fn gemm_q4_0x4_q8_0_neon_sdot(
        group: &[u8],
        acts: &[Q8Activations],
        n_cols: usize,
        out: &mut [f32],
    ) {
        let nb = n_cols / Q4_0_BLOCK_ELEMS;
        let n_acts = acts.len();
        let maskf0 = vdupq_n_u8(0xF0);
        let mut j0 = 0;
        while j0 < n_acts {
            let tile = Q4_0X4_GEMM_NC.min(n_acts - j0);
            let mut acc = [vdupq_n_f32(0.0); Q4_0X4_GEMM_NC];
            for b in 0..nb {
                let blk = group.as_ptr().add(b * Q4_0X4_BLOCK_BYTES);
                let qs = blk.add(8);
                let w = [
                    vld1q_u8(qs),
                    vld1q_u8(qs.add(16)),
                    vld1q_u8(qs.add(32)),
                    vld1q_u8(qs.add(48)),
                ];
                let d_bits = vld1_u16(blk as *const u16);
                let mut dw = [0f32; 4];
                dw[0] = f16::from_bits(vget_lane_u16(d_bits, 0)).to_f32();
                dw[1] = f16::from_bits(vget_lane_u16(d_bits, 1)).to_f32();
                dw[2] = f16::from_bits(vget_lane_u16(d_bits, 2)).to_f32();
                dw[3] = f16::from_bits(vget_lane_u16(d_bits, 3)).to_f32();
                let dw_v = vld1q_f32(dw.as_ptr());

                for t in 0..tile {
                    let act = &acts[j0 + t];
                    let a_ptr = act.q.as_ptr().add(b * Q4_0_BLOCK_ELEMS);
                    let a0 = vld1q_s8(a_ptr);
                    let a1 = vld1q_s8(a_ptr.add(16));
                    let mut ret = vdupq_n_s32(0);
                    for (wi, wchunk) in w.iter().enumerate() {
                        let hi = vreinterpretq_s8_u8(vshlq_n_u8(*wchunk, 4));
                        let lo = vreinterpretq_s8_u8(vandq_u8(*wchunk, maskf0));
                        ret = sdot_lane(ret, hi, a0, wi as u32);
                        ret = sdot_lane(ret, lo, a1, wi as u32);
                    }
                    let scale = vmulq_n_f32(dw_v, act.d[b]);
                    acc[t] = vfmaq_f32(acc[t], vcvtq_f32_s32(vshrq_n_s32(ret, 4)), scale);
                }
            }
            for t in 0..tile {
                let mut lanes = [0f32; Q4_0X4_NROWS];
                vst1q_f32(lanes.as_mut_ptr(), acc[t]);
                for (r, v) in lanes.iter().enumerate() {
                    out[r * n_acts + j0 + t] = *v;
                }
            }
            j0 += tile;
        }
    }

    /// NEON DotProd GEMV for interleave-8 packed Q8_0 weights (llama.cpp
    /// `ggml_gemv_q8_0_4x8_q8_0` in `arch/arm/repack.cpp`). Each 8-byte
    /// activation run is broadcast to both vector halves so one `sdot`
    /// covers two interleaved rows.
    #[target_feature(enable = "neon,dotprod")]
    pub unsafe fn gemv_q8_0x4_q8_0_neon_4x8(
        packed: &[u8],
        act: &Q8Activations,
        n_cols: usize,
        n_row_groups: usize,
        out: &mut [f32],
    ) {
        let nb = n_cols / Q8_0_BLOCK_ELEMS;

        for x in 0..n_row_groups {
            let mut acc = vdupq_n_f32(0.0);
            let group_off = x * nb * Q8_0X4_BLOCK_BYTES;

            for b in 0..nb {
                let blk = packed.as_ptr().add(group_off + b * Q8_0X4_BLOCK_BYTES);
                let qs = blk.add(8) as *const i8;
                let mut d_arr = [0f32; 4];
                for (j, slot) in d_arr.iter_mut().enumerate() {
                    *slot = f16_from_bytes(std::slice::from_raw_parts(blk.add(j * 2), 2));
                }
                let b_d = vld1q_f32(d_arr.as_ptr());
                let a_base = act.q.as_ptr().add(b * Q8_0_BLOCK_ELEMS);

                let mut ret0 = vdupq_n_s32(0);
                let mut ret1 = vdupq_n_s32(0);
                for c in 0..4 {
                    let a = vreinterpretq_s8_s64(vld1q_dup_s64(a_base.add(c * 8) as *const i64));
                    ret0 = sdot(ret0, vld1q_s8(qs.add(c * 32)), a);
                    ret1 = sdot(ret1, vld1q_s8(qs.add(c * 32 + 16)), a);
                }
                let ret = vpaddq_s32(ret0, ret1);

                acc = vfmaq_f32(acc, vcvtq_f32_s32(ret), vmulq_n_f32(b_d, act.d[b]));
            }

            vst1q_f32(out.as_mut_ptr().add(x * Q8_0X4_NROWS), acc);
        }
    }

    /// NEON DotProd GEMV for interleave-8 packed Q4_0 weights (llama.cpp
    /// `ggml_gemv_q4_0_4x8_q8_0` in `arch/arm/repack.cpp`). Nibbles are
    /// consumed at 16× their value (`<< 4` for the low half, `& 0xf0` for
    /// the high half — the pack's 0x88 XOR already folded in the -8), and
    /// the fixed-point convert divides the 16 back out.
    #[target_feature(enable = "neon,dotprod")]
    pub unsafe fn gemv_q4_0x4_q8_0_neon_4x8(
        packed: &[u8],
        act: &Q8Activations,
        n_cols: usize,
        n_row_groups: usize,
        out: &mut [f32],
    ) {
        let nb = n_cols / Q4_0_BLOCK_ELEMS;
        let m4b = vdupq_n_u8(0xf0);

        for x in 0..n_row_groups {
            let mut acc = vdupq_n_f32(0.0);
            let group_off = x * nb * Q4_0X4_BLOCK_BYTES;

            for b in 0..nb {
                let blk = packed.as_ptr().add(group_off + b * Q4_0X4_BLOCK_BYTES);
                let qs = blk.add(8);
                let mut d_arr = [0f32; 4];
                for (j, slot) in d_arr.iter_mut().enumerate() {
                    *slot = f16_from_bytes(std::slice::from_raw_parts(blk.add(j * 2), 2));
                }
                let b_d = vld1q_f32(d_arr.as_ptr());
                let a_base = act.q.as_ptr().add(b * Q4_0_BLOCK_ELEMS);

                let b0 = vld1q_u8(qs);
                let b1 = vld1q_u8(qs.add(16));
                let b2 = vld1q_u8(qs.add(32));
                let b3 = vld1q_u8(qs.add(48));

                let mut a = [vdupq_n_s8(0); 4];
                for (c, slot) in a.iter_mut().enumerate() {
                    *slot = vreinterpretq_s8_s64(vld1q_dup_s64(a_base.add(c * 8) as *const i64));
                }

                let mut ret0 = vdupq_n_s32(0);
                let mut ret1 = vdupq_n_s32(0);
                ret0 = sdot(ret0, vreinterpretq_s8_u8(vshlq_n_u8(b0, 4)), a[0]);
                ret1 = sdot(ret1, vreinterpretq_s8_u8(vshlq_n_u8(b1, 4)), a[0]);
                ret0 = sdot(ret0, vreinterpretq_s8_u8(vshlq_n_u8(b2, 4)), a[1]);
                ret1 = sdot(ret1, vreinterpretq_s8_u8(vshlq_n_u8(b3, 4)), a[1]);
                ret0 = sdot(ret0, vreinterpretq_s8_u8(vandq_u8(b0, m4b)), a[2]);
                ret1 = sdot(ret1, vreinterpretq_s8_u8(vandq_u8(b1, m4b)), a[2]);
                ret0 = sdot(ret0, vreinterpretq_s8_u8(vandq_u8(b2, m4b)), a[3]);
                ret1 = sdot(ret1, vreinterpretq_s8_u8(vandq_u8(b3, m4b)), a[3]);
                let ret = vpaddq_s32(ret0, ret1);

                acc = vfmaq_f32(acc, vcvtq_n_f32_s32::<4>(ret), vmulq_n_f32(b_d, act.d[b]));
            }

            vst1q_f32(out.as_mut_ptr().add(x * Q4_0X4_NROWS), acc);
        }
    }

    /// NEON i8mm **GEMM** for interleave-8 packed Q8_0 weights (llama.cpp
    /// `ggml_gemm_q8_0_4x8_q8_0` in `arch/arm/repack.cpp`, NEON branch).
    /// The activation quad arrives pre-interleaved as [`Q8ActsX4`], so
    /// every `vmmlaq_s32` covers a 2×2 (activation × weight-row) tile.
    #[target_feature(enable = "neon,i8mm")]
    pub unsafe fn gemm_q8_0x4_q8_0_neon_i8mm(
        packed: &[u8],
        tile: &Q8ActsX4,
        n_cols: usize,
        out: &mut [f32],
    ) {
        let na = tile.na;
        debug_assert!(na <= Q8K_ACTS_X4_NC);
        let nb = n_cols / Q8_0_BLOCK_ELEMS;
        debug_assert_eq!(tile.n_blocks, nb);

        // acc_f32[a] holds activation row a's 4 weight-row outputs.
        let mut acc_f32 = [vdupq_n_f32(0.0); Q8K_ACTS_X4_NC];

        for b in 0..nb {
            let blk = packed.as_ptr().add(b * Q8_0X4_BLOCK_BYTES);
            let qs = blk.add(8) as *const i8;
            let a_base = tile.qs.as_ptr().add(b * Q8_0_BLOCK_ELEMS * 4);

            let mut acc = [vdupq_n_s32(0); 4];
            for chunk in 0..4 {
                let a01 = vld1q_s8(a_base.add(chunk * 32));
                let a23 = vld1q_s8(a_base.add(chunk * 32 + 16));
                let b01 = vld1q_s8(qs.add(chunk * 32));
                let b23 = vld1q_s8(qs.add(chunk * 32 + 16));

                acc[0] = vmmla_s32(acc[0], a01, b01);
                acc[1] = vmmla_s32(acc[1], a01, b23);
                acc[2] = vmmla_s32(acc[2], a23, b01);
                acc[3] = vmmla_s32(acc[3], a23, b23);
            }

            // 2×2 tiles → per-activation-row vectors of 4 weight rows.
            let rows = [
                vcombine_s32(vget_low_s32(acc[0]), vget_low_s32(acc[1])),
                vcombine_s32(vget_high_s32(acc[0]), vget_high_s32(acc[1])),
                vcombine_s32(vget_low_s32(acc[2]), vget_low_s32(acc[3])),
                vcombine_s32(vget_high_s32(acc[2]), vget_high_s32(acc[3])),
            ];

            let mut d_arr = [0f32; 4];
            for (j, slot) in d_arr.iter_mut().enumerate() {
                *slot = f16_from_bytes(std::slice::from_raw_parts(blk.add(j * 2), 2));
            }
            let b_d = vld1q_f32(d_arr.as_ptr());

            for a in 0..na {
                acc_f32[a] = vfmaq_f32(
                    acc_f32[a],
                    vcvtq_f32_s32(rows[a]),
                    vmulq_n_f32(b_d, *tile.d.as_ptr().add(b * 4 + a)),
                );
            }
        }

        for a in 0..na {
            let mut lanes = [0f32; Q8_0X4_NROWS];
            vst1q_f32(lanes.as_mut_ptr(), acc_f32[a]);
            for (r, v) in lanes.iter().enumerate() {
                out[r * na + a] = *v;
            }
        }
    }

    /// NEON i8mm **GEMM** for interleave-8 packed Q4_0 weights. llama.cpp
    /// ships `ggml_gemm_q4_0_4x8_q8_0` (`arch/arm/repack.cpp`) as raw
    /// inline asm; this is the same computation with intrinsics, following
    /// the `4x8` GEMV's nibble handling and the Q8_0 GEMM's MMLA tiling.
    #[target_feature(enable = "neon,i8mm")]
    pub unsafe fn gemm_q4_0x4_q8_0_neon_i8mm(
        packed: &[u8],
        tile: &Q8ActsX4,
        n_cols: usize,
        out: &mut [f32],
    ) {
        let na = tile.na;
        debug_assert!(na <= Q8K_ACTS_X4_NC);
        let nb = n_cols / Q4_0_BLOCK_ELEMS;
        debug_assert_eq!(tile.n_blocks, nb);
        let m4b = vdupq_n_u8(0xf0);

        let mut acc_f32 = [vdupq_n_f32(0.0); Q8K_ACTS_X4_NC];

        for b in 0..nb {
            let blk = packed.as_ptr().add(b * Q4_0X4_BLOCK_BYTES);
            let qs = blk.add(8);
            let a_base = tile.qs.as_ptr().add(b * Q4_0_BLOCK_ELEMS * 4);

            let bv = [
                vld1q_u8(qs),
                vld1q_u8(qs.add(16)),
                vld1q_u8(qs.add(32)),
                vld1q_u8(qs.add(48)),
            ];
            // Weight vectors per activation chunk: lo nibbles cover elems
            // 0..16 (chunks 0,1), hi nibbles elems 16..32 (chunks 2,3),
            // all at 16× their value until the fixed-point convert.
            let w = [
                [
                    vreinterpretq_s8_u8(vshlq_n_u8(bv[0], 4)),
                    vreinterpretq_s8_u8(vshlq_n_u8(bv[1], 4)),
                ],
                [
                    vreinterpretq_s8_u8(vshlq_n_u8(bv[2], 4)),
                    vreinterpretq_s8_u8(vshlq_n_u8(bv[3], 4)),
                ],
                [
                    vreinterpretq_s8_u8(vandq_u8(bv[0], m4b)),
                    vreinterpretq_s8_u8(vandq_u8(bv[1], m4b)),
                ],
                [
                    vreinterpretq_s8_u8(vandq_u8(bv[2], m4b)),
                    vreinterpretq_s8_u8(vandq_u8(bv[3], m4b)),
                ],
            ];

            let mut acc = [vdupq_n_s32(0); 4];
            for (chunk, w_pair) in w.iter().enumerate() {
                let a01 = vld1q_s8(a_base.add(chunk * 32));
                let a23 = vld1q_s8(a_base.add(chunk * 32 + 16));

                acc[0] = vmmla_s32(acc[0], a01, w_pair[0]);
                acc[1] = vmmla_s32(acc[1], a01, w_pair[1]);
                acc[2] = vmmla_s32(acc[2], a23, w_pair[0]);
                acc[3] = vmmla_s32(acc[3], a23, w_pair[1]);
            }

            let rows = [
                vcombine_s32(vget_low_s32(acc[0]), vget_low_s32(acc[1])),
                vcombine_s32(vget_high_s32(acc[0]), vget_high_s32(acc[1])),
                vcombine_s32(vget_low_s32(acc[2]), vget_low_s32(acc[3])),
                vcombine_s32(vget_high_s32(acc[2]), vget_high_s32(acc[3])),
            ];

            let mut d_arr = [0f32; 4];
            for (j, slot) in d_arr.iter_mut().enumerate() {
                *slot = f16_from_bytes(std::slice::from_raw_parts(blk.add(j * 2), 2));
            }
            let b_d = vld1q_f32(d_arr.as_ptr());

            for a in 0..na {
                acc_f32[a] = vfmaq_f32(
                    acc_f32[a],
                    vcvtq_n_f32_s32::<4>(rows[a]),
                    vmulq_n_f32(b_d, *tile.d.as_ptr().add(b * 4 + a)),
                );
            }
        }

        for a in 0..na {
            let mut lanes = [0f32; Q4_0X4_NROWS];
            vst1q_f32(lanes.as_mut_ptr(), acc_f32[a]);
            for (r, v) in lanes.iter().enumerate() {
                out[r * na + a] = *v;
            }
        }
    }
}

#[cfg(target_arch = "x86_64")]
mod avx2 {
    use super::*;
    use std::arch::x86_64::*;

    /// AVX2 GEMV for interleave-8 packed weights. Accumulates 8 f32 outputs
    /// in `__m256` lanes; inner int dots use maddubs over nibble×act pairs.
    #[target_feature(enable = "avx2,fma")]
    pub unsafe fn gemv_q4_kx8_q8_k_avx2(
        packed: &[u8],
        act: &Q8KActivations,
        n_cols: usize,
        n_row_groups: usize,
        out: &mut [f32],
    ) {
        let nb = n_cols / Q4_K_BLOCK_ELEMS;
        let blocklen = 8;
        let ncols = Q4_KX8_NROWS;

        for x in 0..n_row_groups {
            let mut acc = _mm256_setzero_ps();
            let mut acc_min = _mm256_setzero_ps();
            let group_off = x * nb * Q4_KX8_BLOCK_BYTES;

            for l in 0..nb {
                let blk = packed.as_ptr().add(group_off + l * Q4_KX8_BLOCK_BYTES);
                let mut d_arr = [0f32; 8];
                let mut dmin_arr = [0f32; 8];
                for j in 0..8 {
                    d_arr[j] = f16_from_bytes(std::slice::from_raw_parts(blk.add(j * 2), 2));
                    dmin_arr[j] =
                        f16_from_bytes(std::slice::from_raw_parts(blk.add(16 + j * 2), 2));
                }
                let da = act.d[l];
                let d_vec = _mm256_mul_ps(_mm256_loadu_ps(d_arr.as_ptr()), _mm256_set1_ps(da));
                let dmin_vec =
                    _mm256_mul_ps(_mm256_loadu_ps(dmin_arr.as_ptr()), _mm256_set1_ps(da));

                let scales = std::slice::from_raw_parts(blk.add(32), 96);
                let qs = std::slice::from_raw_parts(blk.add(128), 1024);
                let q8 = &act.q[l * Q4_K_BLOCK_ELEMS..(l + 1) * Q4_K_BLOCK_ELEMS];
                let bsums = &act.bsums[l * 16..(l + 1) * 16];

                let mut all_scales = [[0u8; 8]; 8];
                let mut all_mins = [[0u8; 8]; 8];
                for sb in 0..8 {
                    decode_scales_mins(&scales[sb * 12..], &mut all_scales[sb], &mut all_mins[sb]);
                }

                let mut isum = [0i32; 8];
                let n_k = Q4_K_BLOCK_ELEMS / (2 * blocklen);
                for k in 0..n_k {
                    let sb_pair = k / 4;
                    let sc0 = &all_scales[sb_pair * 2];
                    let sc1 = &all_scales[sb_pair * 2 + 1];
                    for j in 0..ncols {
                        let mut s = 0i32;
                        for i in 0..blocklen {
                            let qbyte = qs[k * ncols * blocklen + j * blocklen + i];
                            let v0 = (qbyte & 0x0F) as i32;
                            let v1 = (qbyte >> 4) as i32;
                            let a0 = q8[(k >> 2) * 64 + (k % 4) * blocklen + i] as i32;
                            let a1 = q8[(k >> 2) * 64 + (k % 4) * blocklen + i + 32] as i32;
                            s += v0 * a0 * sc0[j] as i32 + v1 * a1 * sc1[j] as i32;
                        }
                        isum[j] += s;
                    }
                }

                let isum_ps =
                    _mm256_cvtepi32_ps(_mm256_loadu_si256(isum.as_ptr() as *const __m256i));
                acc = _mm256_fmadd_ps(isum_ps, d_vec, acc);

                let mut minsum = [0i32; 8];
                for sb in 0..8 {
                    let bsum = bsums[sb * 2] as i32 + bsums[sb * 2 + 1] as i32;
                    for j in 0..ncols {
                        minsum[j] += all_mins[sb][j] as i32 * bsum;
                    }
                }
                let minsum_ps =
                    _mm256_cvtepi32_ps(_mm256_loadu_si256(minsum.as_ptr() as *const __m256i));
                acc_min = _mm256_fmadd_ps(minsum_ps, dmin_vec, acc_min);
            }

            _mm256_storeu_ps(out.as_mut_ptr().add(x * ncols), _mm256_sub_ps(acc, acc_min));
        }
    }
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::{
        dot_q4_0_q8_scalar, dot_q4_k_q8_scalar, dot_q5_k_q8_scalar, dot_q6_k_q8_scalar,
        dot_q8_0_q8_scalar, quantize_activations_q8, quantize_activations_q8_k, Q4_0_BLOCK_BYTES,
        Q5_K_BLOCK_BYTES, Q6_K_BLOCK_BYTES,
    };

    fn synth_q5_k_row(n_blocks: usize, seed: u8) -> Vec<u8> {
        let mut weights = Vec::with_capacity(n_blocks * Q5_K_BLOCK_BYTES);
        for b in 0..n_blocks {
            weights.extend_from_slice(
                &f16::from_f32(0.05 + (b as f32 + seed as f32) * 0.01).to_le_bytes(),
            );
            weights.extend_from_slice(
                &f16::from_f32(0.01 + (b as f32 + seed as f32) * 0.002).to_le_bytes(),
            );
            for i in 0..12u8 {
                weights.push(20 + i.wrapping_mul(3).wrapping_add(seed));
            }
            for i in 0..32u8 {
                weights.push(i.wrapping_mul(11).wrapping_add(b as u8).wrapping_add(seed));
            }
            for i in 0..128u8 {
                weights.push(i.wrapping_mul(19).wrapping_add(b as u8).wrapping_add(seed));
            }
        }
        weights
    }

    fn synth_q6_k_row(n_blocks: usize, seed: u8) -> Vec<u8> {
        let mut weights = Vec::with_capacity(n_blocks * Q6_K_BLOCK_BYTES);
        for b in 0..n_blocks {
            for i in 0..128u8 {
                weights.push(i.wrapping_mul(17).wrapping_add(b as u8).wrapping_add(seed));
            }
            for i in 0..64u8 {
                weights.push(i.wrapping_mul(13).wrapping_add(seed).wrapping_add(b as u8));
            }
            for i in 0..16u8 {
                // signed scales in -32..31-ish
                weights.push((20i8).wrapping_add(i as i8).wrapping_add(seed as i8) as u8);
            }
            weights.extend_from_slice(
                &f16::from_f32(0.04 + (b as f32 + seed as f32) * 0.008).to_le_bytes(),
            );
        }
        weights
    }

    fn synth_q4_k_row(n_blocks: usize, seed: u8) -> Vec<u8> {
        let mut weights = Vec::with_capacity(n_blocks * Q4_K_BLOCK_BYTES);
        for b in 0..n_blocks {
            weights.extend_from_slice(
                &f16::from_f32(0.05 + (b as f32 + seed as f32) * 0.01).to_le_bytes(),
            );
            weights.extend_from_slice(
                &f16::from_f32(0.01 + (b as f32 + seed as f32) * 0.002).to_le_bytes(),
            );
            for i in 0..12u8 {
                weights.push(20 + i.wrapping_mul(3).wrapping_add(seed));
            }
            for i in 0..128u8 {
                weights.push(i.wrapping_mul(17).wrapping_add(b as u8).wrapping_add(seed));
            }
        }
        weights
    }

    fn synth_q4_0_row(n_blocks: usize, seed: u8) -> Vec<u8> {
        let mut weights = Vec::with_capacity(n_blocks * Q4_0_BLOCK_BYTES);
        for b in 0..n_blocks {
            weights.extend_from_slice(
                &f16::from_f32(0.05 + (b as f32 + seed as f32) * 0.012).to_le_bytes(),
            );
            for i in 0..16u8 {
                weights.push(i.wrapping_mul(23).wrapping_add(b as u8).wrapping_add(seed));
            }
        }
        weights
    }

    fn synth_q8_0_row(n_blocks: usize, seed: u8) -> Vec<u8> {
        let mut weights = Vec::with_capacity(n_blocks * Q8_0_BLOCK_BYTES);
        for b in 0..n_blocks {
            weights.extend_from_slice(
                &f16::from_f32(0.04 + (b as f32 + seed as f32) * 0.008).to_le_bytes(),
            );
            for i in 0..32u8 {
                // signed i8 stored as u8 bytes
                let q = ((i as i8)
                    .wrapping_mul(3)
                    .wrapping_add(seed as i8)
                    .wrapping_add(b as i8)) as u8;
                weights.push(q);
            }
        }
        weights
    }

    #[test]
    fn pack_and_gemv_matches_scalar_row_dots() {
        let n_blocks = 2;
        let cols = n_blocks * Q4_K_BLOCK_ELEMS;
        let rows = 16; // two full groups
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q4_k_row(n_blocks, r as u8));
        }
        let x: Vec<f32> = (0..cols)
            .map(|i| ((i as f32) * 0.017 - 2.1).sin() * 1.8)
            .collect();
        let act = quantize_activations_q8_k(&x);

        let mut reference = vec![0f32; rows];
        let row_bytes = n_blocks * Q4_K_BLOCK_BYTES;
        for r in 0..rows {
            reference[r] = dot_q4_k_q8_scalar(&matrix[r * row_bytes..(r + 1) * row_bytes], &act);
        }

        for &interleave in &[4usize, 8] {
            let packed = pack_q4_k_matrix_x8(&matrix, rows, cols, interleave);
            let n_groups = rows / Q4_KX8_NROWS;
            let mut out = vec![0f32; rows];
            gemv_q4_kx8_q8_k(&packed, &act, cols, n_groups, interleave, &mut out);
            for r in 0..rows {
                let err = (out[r] - reference[r]).abs();
                let scale = reference[r].abs().max(1.0);
                assert!(
                    err / scale < 1e-4 || err < 1e-3,
                    "interleave={interleave} row {r}: got {} want {} err={err}",
                    out[r],
                    reference[r]
                );
            }
        }
    }

    #[test]
    fn q4_0x4_pack_and_gemv_matches_scalar_row_dots() {
        let n_blocks = 3;
        let cols = n_blocks * Q4_0_BLOCK_ELEMS;
        let rows = 12;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q4_0_row(n_blocks, r as u8));
        }
        let x: Vec<f32> = (0..cols)
            .map(|i| ((i as f32) * 0.019 - 1.2).sin() * 2.1)
            .collect();
        let act = quantize_activations_q8(&x);

        let row_bytes = n_blocks * Q4_0_BLOCK_BYTES;
        let mut reference = vec![0f32; rows];
        for r in 0..rows {
            reference[r] = dot_q4_0_q8_scalar(&matrix[r * row_bytes..(r + 1) * row_bytes], &act);
        }

        for &interleave in &[4usize, 8] {
            let packed = pack_q4_0_matrix_x4(&matrix, rows, cols, interleave);
            let n_groups = rows / Q4_0X4_NROWS;
            let mut out = vec![0f32; rows];
            gemv_q4_0x4_q8_0(&packed, &act, cols, n_groups, interleave, &mut out);
            for r in 0..rows {
                let err = (out[r] - reference[r]).abs();
                let scale = reference[r].abs().max(1.0);
                assert!(
                    err / scale < 1e-4 || err < 1e-3,
                    "Q4_0x4 interleave={interleave} row {r}: got {} want {} err={err}",
                    out[r],
                    reference[r]
                );
            }
        }
    }

    #[test]
    fn q4_0x4_gemm_matches_the_gemv_run_once_per_activation() {
        let n_blocks = 4;
        let cols = n_blocks * Q4_0_BLOCK_ELEMS;
        let rows = 8;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q4_0_row(n_blocks, (r * 2 + 5) as u8));
        }
        let packed = pack_q4_0_matrix_x4(&matrix, rows, cols, Q4_0X4_INTERLEAVE);

        let n_acts = 7;
        let acts: Vec<Q8Activations> = (0..n_acts)
            .map(|j| {
                let x: Vec<f32> = (0..cols)
                    .map(|i| (((i + j * 11) as f32) * 0.021 - 0.7).cos() * 1.9)
                    .collect();
                quantize_activations_q8(&x)
            })
            .collect();

        for group in 0..rows / Q4_0X4_NROWS {
            let mut gemm_out = vec![0f32; Q4_0X4_NROWS * n_acts];
            gemm_q4_0x4_group(
                &packed,
                group,
                &acts,
                cols,
                Q4_0X4_INTERLEAVE,
                &mut gemm_out,
            );

            for (j, act) in acts.iter().enumerate() {
                let mut gemv_out = [0f32; Q4_0X4_NROWS];
                gemv_q4_0x4_group(&packed, group, act, cols, Q4_0X4_INTERLEAVE, &mut gemv_out);
                for r in 0..Q4_0X4_NROWS {
                    assert_eq!(
                        gemm_out[r * n_acts + j],
                        gemv_out[r],
                        "group {group} row {r} act {j}: Q4_0 GEMM and GEMV disagree"
                    );
                }
            }
        }
    }

    #[test]
    fn q4_0x4_gemm_with_no_activations_is_a_no_op() {
        let n_blocks = 2;
        let cols = n_blocks * Q4_0_BLOCK_ELEMS;
        let mut matrix = Vec::new();
        for r in 0..Q4_0X4_NROWS {
            matrix.extend_from_slice(&synth_q4_0_row(n_blocks, r as u8));
        }
        let packed = pack_q4_0_matrix_x4(&matrix, Q4_0X4_NROWS, cols, Q4_0X4_INTERLEAVE);
        let mut out: Vec<f32> = Vec::new();
        gemm_q4_0x4_group(&packed, 0, &[], cols, Q4_0X4_INTERLEAVE, &mut out);
        assert!(out.is_empty());
    }

    #[test]
    fn q8_0x4_pack_and_gemv_matches_scalar_row_dots() {
        let n_blocks = 3;
        let cols = n_blocks * Q8_0_BLOCK_ELEMS;
        let rows = 12; // three full groups of 4
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q8_0_row(n_blocks, r as u8));
        }
        let x: Vec<f32> = (0..cols)
            .map(|i| ((i as f32) * 0.023 - 1.4).cos() * 2.2)
            .collect();
        let act = quantize_activations_q8(&x);

        let row_bytes = n_blocks * Q8_0_BLOCK_BYTES;
        let mut reference = vec![0f32; rows];
        for r in 0..rows {
            reference[r] = dot_q8_0_q8_scalar(&matrix[r * row_bytes..(r + 1) * row_bytes], &act);
        }

        for &interleave in &[4usize, 8] {
            let packed = pack_q8_0_matrix_x4(&matrix, rows, cols, interleave);
            let n_groups = rows / Q8_0X4_NROWS;
            let mut out = vec![0f32; rows];
            gemv_q8_0x4_q8_0(&packed, &act, cols, n_groups, interleave, &mut out);
            for r in 0..rows {
                let err = (out[r] - reference[r]).abs();
                let scale = reference[r].abs().max(1.0);
                assert!(
                    err / scale < 1e-4 || err < 1e-3,
                    "Q8_0x4 interleave={interleave} row {r}: got {} want {} err={err}",
                    out[r],
                    reference[r]
                );
            }
        }
    }

    /// The GEMM exists purely to reuse weight loads across activations,
    /// so it must produce exactly what the per-activation GEMV produces
    /// -- not merely something close. Any divergence would be a
    /// batch-size-dependent numeric difference, i.e. prefill and decode
    /// disagreeing about the same prompt.
    #[test]
    fn q8_0x4_gemm_matches_the_gemv_run_once_per_activation() {
        let n_blocks = 4;
        let cols = n_blocks * Q8_0_BLOCK_ELEMS;
        let rows = 8;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q8_0_row(n_blocks, (r * 3 + 1) as u8));
        }
        let packed = pack_q8_0_matrix_x4(&matrix, rows, cols, Q8_0X4_INTERLEAVE);

        // Deliberately not a multiple of the tile width, so the tail
        // path is covered too.
        let n_acts = 7;
        let acts: Vec<Q8Activations> = (0..n_acts)
            .map(|j| {
                let x: Vec<f32> = (0..cols)
                    .map(|i| (((i + j * 13) as f32) * 0.017 - 0.9).sin() * 1.7)
                    .collect();
                quantize_activations_q8(&x)
            })
            .collect();

        for group in 0..rows / Q8_0X4_NROWS {
            let mut gemm_out = vec![0f32; Q8_0X4_NROWS * n_acts];
            gemm_q8_0x4_group(
                &packed,
                group,
                &acts,
                cols,
                Q8_0X4_INTERLEAVE,
                &mut gemm_out,
            );

            for (j, act) in acts.iter().enumerate() {
                let mut gemv_out = [0f32; Q8_0X4_NROWS];
                gemv_q8_0x4_group(&packed, group, act, cols, Q8_0X4_INTERLEAVE, &mut gemv_out);
                for r in 0..Q8_0X4_NROWS {
                    assert_eq!(
                        gemm_out[r * n_acts + j],
                        gemv_out[r],
                        "group {group} row {r} act {j}: GEMM and GEMV disagree"
                    );
                }
            }
        }
    }

    /// The Q4_K GEMM must agree with the GEMV **exactly**, for the same
    /// reason as the Q8_0 pair above: the two run on the same prompt in
    /// different batch regimes (prefill vs the `< 4` tail vs decode), so
    /// any divergence is prefill and decode disagreeing about the same
    /// tokens. The GEMM only reorders which loop the weight unpack sits
    /// in — every multiply-accumulate happens in the same order and the
    /// same precision — so equality is the right assertion, not
    /// closeness.
    #[test]
    fn q4_kx8_gemm_matches_the_gemv_run_once_per_activation() {
        let n_blocks = 3;
        let cols = n_blocks * Q4_K_BLOCK_ELEMS;
        let rows = 2 * Q4_KX8_NROWS;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q4_k_row(n_blocks, (r * 5 + 3) as u8));
        }
        let interleave = q4_kx8_interleave();
        let packed = pack_q4_k_matrix_x8(&matrix, rows, cols, interleave);

        // Not a multiple of the tile width, so the ragged tail the
        // caller has to chunk around is covered too.
        let n_acts = 6;
        let acts: Vec<Q8KActivations> = (0..n_acts)
            .map(|j| {
                let x: Vec<f32> = (0..cols)
                    .map(|i| (((i + j * 29) as f32) * 0.011 - 0.4).cos() * 2.3)
                    .collect();
                quantize_activations_q8_k(&x)
            })
            .collect();

        for group in 0..rows / Q4_KX8_NROWS {
            for chunk in acts.chunks(Q4_KX8_GEMM_NC) {
                let mut gemm_out = vec![0f32; Q4_KX8_NROWS * chunk.len()];
                gemm_q4_kx8_group(&packed, group, chunk, cols, interleave, &mut gemm_out);

                for (j, act) in chunk.iter().enumerate() {
                    let mut gemv_out = [0f32; Q4_KX8_NROWS];
                    gemv_q4_kx8_group(&packed, group, act, cols, interleave, &mut gemv_out);
                    for r in 0..Q4_KX8_NROWS {
                        let got = gemm_out[r * chunk.len() + j];
                        let want = gemv_out[r];
                        if interleave == 4 {
                            assert_eq!(
                                got, want,
                                "group {group} row {r} act {j}: Q4_K GEMM and GEMV disagree"
                            );
                        } else {
                            let err = (got - want).abs();
                            let scale = want.abs().max(1.0);
                            assert!(
                                err / scale < 1e-4 || err < 1e-2,
                                "group {group} row {r} act {j}: GEMM {got} vs GEMV {want} (err={err})"
                            );
                        }
                    }
                }
            }
        }
    }

    #[test]
    #[cfg(target_arch = "aarch64")]
    fn q4_kx8_gemm_i8mm_matches_scalar_when_available() {
        if !std::arch::is_aarch64_feature_detected!("i8mm") {
            return;
        }
        let interleave = q4_kx8_interleave();
        assert_eq!(interleave, 8, "i8mm host should pack with interleave 8");

        let n_blocks = 3;
        let cols = n_blocks * Q4_K_BLOCK_ELEMS;
        let rows = Q4_KX8_NROWS;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q4_k_row(n_blocks, (r * 7 + 2) as u8));
        }
        let packed = pack_q4_k_matrix_x8(&matrix, rows, cols, interleave);

        let n_acts = 4;
        let acts: Vec<Q8KActivations> = (0..n_acts)
            .map(|j| {
                let x: Vec<f32> = (0..cols)
                    .map(|i| (((i + j * 17) as f32) * 0.013 - 0.6).sin() * 1.9)
                    .collect();
                quantize_activations_q8_k(&x)
            })
            .collect();

        let mut gemm_out = vec![0f32; Q4_KX8_NROWS * n_acts];
        gemm_q4_kx8_group(&packed, 0, &acts, cols, interleave, &mut gemm_out);

        for (j, act) in acts.iter().enumerate() {
            let mut scalar_out = [0f32; Q4_KX8_NROWS];
            gemv_q4_kx8_group(&packed, 0, act, cols, interleave, &mut scalar_out);
            for r in 0..Q4_KX8_NROWS {
                let got = gemm_out[r * n_acts + j];
                let want = scalar_out[r];
                let err = (got - want).abs();
                let scale = want.abs().max(1.0);
                assert!(
                    err / scale < 1e-5 || err < 1e-3,
                    "row {r} act {j}: i8mm GEMM {got} vs scalar {want} (err={err})"
                );
            }
        }
    }

    fn synth_q8_k_acts(n: usize, cols: usize) -> Vec<Q8KActivations> {
        (0..n)
            .map(|j| {
                let x: Vec<f32> = (0..cols)
                    .map(|i| (((i + j * 17) as f32) * 0.013 - 0.6).sin() * 1.9)
                    .collect();
                quantize_activations_q8_k(&x)
            })
            .collect()
    }

    /// The retired per-block interleave (`pack_q8_k_qs_x4_i8`), kept verbatim
    /// as the reference `prepare_q8_k_acts_x4` must reproduce: llama.cpp's
    /// `ggml_quantize_mat_q8_K_4x8` qs ordering with 8-byte runs.
    fn reference_q8_kx4_block_qs(
        acts: &[Q8KActivations],
        block: usize,
    ) -> [i8; Q4_K_BLOCK_ELEMS * 4] {
        const BLCK: usize = 8;
        let na = acts.len();
        let mut out = [0i8; Q4_K_BLOCK_ELEMS * 4];
        for (j, slot) in out.iter_mut().enumerate() {
            let src_offset = (j / (4 * BLCK)) * BLCK + (j % BLCK);
            let src_id = (j % (4 * BLCK)) / BLCK;
            *slot = if src_id < na {
                acts[src_id].q[block * Q4_K_BLOCK_ELEMS + src_offset]
            } else {
                0
            };
        }
        out
    }

    #[test]
    fn prepare_q8_k_acts_x4_matches_block_interleave_reference() {
        let n_blocks = 3;
        let cols = n_blocks * Q4_K_BLOCK_ELEMS;
        for na in 1..=Q4_KX8_GEMM_NC {
            let acts = synth_q8_k_acts(na, cols);
            let tile = prepare_q8_k_acts_x4(&acts, cols);
            assert_eq!(tile.na, na);
            assert_eq!(tile.n_blocks, n_blocks);
            for b in 0..n_blocks {
                let want_qs = reference_q8_kx4_block_qs(&acts, b);
                assert_eq!(
                    &tile.qs[b * Q4_K_BLOCK_ELEMS * 4..][..Q4_K_BLOCK_ELEMS * 4],
                    &want_qs[..],
                    "qs mismatch, block {b} na {na}"
                );
                for a in 0..4 {
                    let act = acts.get(a);
                    for i in 0..8 {
                        let want = act.map_or(0, |act| {
                            act.bsums[b * 16 + 2 * i] + act.bsums[b * 16 + 2 * i + 1]
                        });
                        assert_eq!(
                            tile.bsums[(b * 4 + a) * 8 + i],
                            want,
                            "bsums mismatch, block {b} row {a} pair {i} na {na}"
                        );
                    }
                    let want_d = act.map_or(0.0, |act| act.d[b]);
                    assert_eq!(tile.d[b * 4 + a], want_d, "d mismatch, block {b} row {a}");
                }
            }
        }
    }

    #[test]
    fn q4_kx8_gemm_x4_portable_is_bit_exact_vs_scalar_gemv() {
        let n_blocks = 3;
        let cols = n_blocks * Q4_K_BLOCK_ELEMS;
        let rows = Q4_KX8_NROWS;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q4_k_row(n_blocks, (r * 5 + 3) as u8));
        }
        let packed = pack_q4_k_matrix_x8(&matrix, rows, cols, 8);

        for na in 1..=Q4_KX8_GEMM_NC {
            let acts = synth_q8_k_acts(na, cols);
            let tile = prepare_q8_k_acts_x4(&acts, cols);
            let mut got = vec![0f32; Q4_KX8_NROWS * na];
            gemm_q4_kx8_acts_x4_scalar_8(&packed, &tile, cols, &mut got);

            for (j, act) in acts.iter().enumerate() {
                let mut want = [0f32; Q4_KX8_NROWS];
                gemv_q4_kx8_q8_k_scalar_8(&packed, act, cols, 1, &mut want);
                for r in 0..Q4_KX8_NROWS {
                    assert_eq!(
                        got[r * na + j].to_bits(),
                        want[r].to_bits(),
                        "row {r} act {j} na {na}: x4 {} vs GEMV {}",
                        got[r * na + j],
                        want[r]
                    );
                }
            }
        }
    }

    /// The hoisted path must reproduce the in-kernel-interleave behavior it
    /// replaced: `gemm_q4_kx8_group` (which now prepares the quad per call)
    /// and `gemm_q4_kx8_group_x4` (quad prepared by the caller) share the
    /// i8mm kernel, so their outputs must be bit-identical, and both must
    /// match the scalar GEMV within the usual tolerance.
    #[test]
    #[cfg(target_arch = "aarch64")]
    fn q4_kx8_gemm_x4_i8mm_matches_group_and_scalar() {
        if !std::arch::is_aarch64_feature_detected!("i8mm") {
            return;
        }
        let interleave = q4_kx8_interleave();
        assert_eq!(interleave, 8, "i8mm host should pack with interleave 8");

        let n_blocks = 3;
        let cols = n_blocks * Q4_K_BLOCK_ELEMS;
        let rows = Q4_KX8_NROWS;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q4_k_row(n_blocks, (r * 7 + 2) as u8));
        }
        let packed = pack_q4_k_matrix_x8(&matrix, rows, cols, interleave);

        assert!(q4_kx8_gemm_uses_acts_x4(interleave));
        for na in 1..=Q4_KX8_GEMM_NC {
            let acts = synth_q8_k_acts(na, cols);
            let tile = prepare_q8_k_acts_x4(&acts, cols);

            let mut x4_out = vec![0f32; Q4_KX8_NROWS * na];
            gemm_q4_kx8_group_x4(&packed, 0, &tile, cols, interleave, &mut x4_out);

            let mut group_out = vec![0f32; Q4_KX8_NROWS * na];
            gemm_q4_kx8_group(&packed, 0, &acts, cols, interleave, &mut group_out);
            assert_eq!(
                x4_out.iter().map(|v| v.to_bits()).collect::<Vec<_>>(),
                group_out.iter().map(|v| v.to_bits()).collect::<Vec<_>>(),
                "x4 entry diverged from the compat entry, na {na}"
            );

            for (j, act) in acts.iter().enumerate() {
                let mut scalar_out = [0f32; Q4_KX8_NROWS];
                gemv_q4_kx8_group(&packed, 0, act, cols, interleave, &mut scalar_out);
                for r in 0..Q4_KX8_NROWS {
                    let got = x4_out[r * na + j];
                    let want = scalar_out[r];
                    let err = (got - want).abs();
                    let scale = want.abs().max(1.0);
                    assert!(
                        err / scale < 1e-5 || err < 1e-3,
                        "row {r} act {j} na {na}: i8mm x4 GEMM {got} vs scalar {want} (err={err})"
                    );
                }
            }
        }
    }

    #[test]
    fn q5_kx8_gemm_x4_portable_is_bit_exact_vs_scalar_gemv() {
        let n_blocks = 3;
        let cols = n_blocks * Q5_K_BLOCK_ELEMS;
        let rows = Q5_KX8_NROWS;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q5_k_row(n_blocks, (r * 5 + 3) as u8));
        }
        let packed = pack_q5_k_matrix_x8(&matrix, rows, cols, 8);

        for na in 1..=Q5_KX8_GEMM_NC {
            let acts = synth_q8_k_acts(na, cols);
            let tile = prepare_q8_k_acts_x4(&acts, cols);
            let mut got = vec![0f32; Q5_KX8_NROWS * na];
            gemm_q5_kx8_acts_x4_scalar_8(&packed, &tile, cols, &mut got);

            for (j, act) in acts.iter().enumerate() {
                let mut want = [0f32; Q5_KX8_NROWS];
                gemv_q5_kx8_q8_k_scalar_8(&packed, act, cols, 1, &mut want);
                for r in 0..Q5_KX8_NROWS {
                    assert_eq!(
                        got[r * na + j].to_bits(),
                        want[r].to_bits(),
                        "row {r} act {j} na {na}: x4 {} vs GEMV {}",
                        got[r * na + j],
                        want[r]
                    );
                }
            }
        }
    }

    #[test]
    fn q6_kx8_gemm_x4_portable_is_bit_exact_vs_scalar_gemv() {
        let n_blocks = 2;
        let cols = n_blocks * Q6_K_BLOCK_ELEMS;
        let rows = Q6_KX8_NROWS;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q6_k_row(n_blocks, (r * 3 + 2) as u8));
        }
        let packed = pack_q6_k_matrix_x8(&matrix, rows, cols, 8);

        for na in 1..=Q8K_ACTS_X4_NC {
            let acts = synth_q8_k_acts(na, cols);
            let tile = prepare_q8_k_acts_x4(&acts, cols);
            let mut got = vec![0f32; Q6_KX8_NROWS * na];
            gemm_q6_kx8_acts_x4_scalar_8(&packed, &tile, cols, &mut got);

            for (j, act) in acts.iter().enumerate() {
                let mut want = [0f32; Q6_KX8_NROWS];
                gemv_q6_kx8_q8_k_scalar(&packed, act, cols, 1, 8, &mut want);
                for r in 0..Q6_KX8_NROWS {
                    assert_eq!(
                        got[r * na + j].to_bits(),
                        want[r].to_bits(),
                        "row {r} act {j} na {na}: x4 {} vs GEMV {}",
                        got[r * na + j],
                        want[r]
                    );
                }
            }
        }
    }

    /// The interleave-8 DotProd GEMV against the scalar interleave-8
    /// reference (the i8mm GEMM side of Q4_K is covered above).
    #[test]
    #[cfg(target_arch = "aarch64")]
    fn q4_kx8_interleave8_neon_gemv_matches_scalar_when_available() {
        if !std::arch::is_aarch64_feature_detected!("dotprod") {
            return;
        }
        let n_blocks = 3;
        let cols = n_blocks * Q4_K_BLOCK_ELEMS;
        let n_groups = 2;
        let rows = n_groups * Q4_KX8_NROWS;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q4_k_row(n_blocks, (r * 11 + 5) as u8));
        }
        let packed = pack_q4_k_matrix_x8(&matrix, rows, cols, 8);

        let acts = synth_q8_k_acts(4, cols);
        for act in &acts {
            let mut got = vec![0f32; rows];
            gemv_q4_kx8_q8_k(&packed, act, cols, n_groups, 8, &mut got);
            let mut want = vec![0f32; rows];
            gemv_q4_kx8_q8_k_scalar_8(&packed, act, cols, n_groups, &mut want);
            for r in 0..rows {
                let err = (got[r] - want[r]).abs();
                // Tolerance, not bit equality: the int8 dots are exact in
                // i32, but the two paths fold the per-sub-block f32
                // scales in a different order, so the f32 accumulation
                // rounds differently. Measured on an M2 Pro (the first
                // i8mm host this ever ran on): 63 of 64 outputs agree to
                // <= 6.3e-6 relative, one to 2.6e-5. 5e-5 keeps a margin
                // over that while still being orders of magnitude
                // tighter than any indexing error, which moves a result
                // by the size of the data. Cross-checked end to end:
                // greedy CPU generation with these kernels is
                // token-identical to `FERROX_CPU_INT_DOT=0`.
                assert!(
                    err / want[r].abs().max(1.0) < 5e-5 || err < 1e-3,
                    "gemv row {r}: NEON 8x8 {} vs scalar {}",
                    got[r],
                    want[r]
                );
            }
        }
    }

    /// The interleave-8 NEON paths (DotProd 8x8 GEMV, i8mm GEMM) against
    /// the scalar interleave-8 references, plus the x4 entry against the
    /// compat entry (bit-exact -- they share the kernel).
    #[test]
    #[cfg(target_arch = "aarch64")]
    fn q5_kx8_interleave8_neon_matches_references_when_available() {
        if !std::arch::is_aarch64_feature_detected!("dotprod") {
            return;
        }
        let n_blocks = 3;
        let cols = n_blocks * Q5_K_BLOCK_ELEMS;
        let n_groups = 2;
        let rows = n_groups * Q5_KX8_NROWS;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q5_k_row(n_blocks, (r * 7 + 1) as u8));
        }
        let packed = pack_q5_k_matrix_x8(&matrix, rows, cols, 8);

        let acts = synth_q8_k_acts(4, cols);
        for act in &acts {
            let mut got = vec![0f32; rows];
            gemv_q5_kx8_q8_k(&packed, act, cols, n_groups, 8, &mut got);
            let mut want = vec![0f32; rows];
            gemv_q5_kx8_q8_k_scalar_8(&packed, act, cols, n_groups, &mut want);
            for r in 0..rows {
                let err = (got[r] - want[r]).abs();
                // Tolerance, not bit equality: the int8 dots are exact in
                // i32, but the two paths fold the per-sub-block f32
                // scales in a different order, so the f32 accumulation
                // rounds differently. Measured on an M2 Pro (the first
                // i8mm host this ever ran on): 63 of 64 outputs agree to
                // <= 6.3e-6 relative, one to 2.6e-5. 5e-5 keeps a margin
                // over that while still being orders of magnitude
                // tighter than any indexing error, which moves a result
                // by the size of the data. Cross-checked end to end:
                // greedy CPU generation with these kernels is
                // token-identical to `FERROX_CPU_INT_DOT=0`.
                assert!(
                    err / want[r].abs().max(1.0) < 5e-5 || err < 1e-3,
                    "gemv row {r}: NEON 8x8 {} vs scalar {}",
                    got[r],
                    want[r]
                );
            }
        }

        if !std::arch::is_aarch64_feature_detected!("i8mm") {
            return;
        }
        for na in 1..=Q5_KX8_GEMM_NC {
            let acts = synth_q8_k_acts(na, cols);
            let tile = prepare_q8_k_acts_x4(&acts, cols);
            for group in 0..n_groups {
                let mut x4_out = vec![0f32; Q5_KX8_NROWS * na];
                gemm_q5_kx8_group_x4(&packed, group, &tile, cols, 8, &mut x4_out);

                let mut group_out = vec![0f32; Q5_KX8_NROWS * na];
                gemm_q5_kx8_group(&packed, group, &acts, cols, 8, &mut group_out);
                assert_eq!(
                    x4_out.iter().map(|v| v.to_bits()).collect::<Vec<_>>(),
                    group_out.iter().map(|v| v.to_bits()).collect::<Vec<_>>(),
                    "x4 entry diverged from the compat entry, group {group} na {na}"
                );

                let nb = cols / Q5_K_BLOCK_ELEMS;
                let slice = &packed[group * nb * Q5_KX8_BLOCK_BYTES..][..nb * Q5_KX8_BLOCK_BYTES];
                let mut want = vec![0f32; Q5_KX8_NROWS * na];
                gemm_q5_kx8_acts_x4_scalar_8(slice, &tile, cols, &mut want);
                for (got, want) in x4_out.iter().zip(want.iter()) {
                    let err = (got - want).abs();
                    // Same 5e-5 as the GEMV check above, for the same
                    // reason: i8mm folds the f32 scales in a different
                    // order than the portable path, and the worst
                    // deviation measured on an i8mm host is 2.6e-5.
                    assert!(
                        err / want.abs().max(1.0) < 5e-5 || err < 1e-3,
                        "group {group} na {na}: i8mm GEMM {got} vs portable {want}"
                    );
                }
            }
        }
    }

    /// Q6_K twin of the test above.
    #[test]
    #[cfg(target_arch = "aarch64")]
    fn q6_kx8_interleave8_neon_matches_references_when_available() {
        if !std::arch::is_aarch64_feature_detected!("dotprod") {
            return;
        }
        let n_blocks = 2;
        let cols = n_blocks * Q6_K_BLOCK_ELEMS;
        let n_groups = 2;
        let rows = n_groups * Q6_KX8_NROWS;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q6_k_row(n_blocks, (r * 9 + 4) as u8));
        }
        let packed = pack_q6_k_matrix_x8(&matrix, rows, cols, 8);

        let acts = synth_q8_k_acts(4, cols);
        for act in &acts {
            let mut got = vec![0f32; rows];
            gemv_q6_kx8_q8_k(&packed, act, cols, n_groups, 8, &mut got);
            let mut want = vec![0f32; rows];
            gemv_q6_kx8_q8_k_scalar(&packed, act, cols, n_groups, 8, &mut want);
            for r in 0..rows {
                let err = (got[r] - want[r]).abs();
                // Tolerance, not bit equality: the int8 dots are exact in
                // i32, but the two paths fold the per-sub-block f32
                // scales in a different order, so the f32 accumulation
                // rounds differently. Measured on an M2 Pro (the first
                // i8mm host this ever ran on): 63 of 64 outputs agree to
                // <= 6.3e-6 relative, one to 2.6e-5. 5e-5 keeps a margin
                // over that while still being orders of magnitude
                // tighter than any indexing error, which moves a result
                // by the size of the data. Cross-checked end to end:
                // greedy CPU generation with these kernels is
                // token-identical to `FERROX_CPU_INT_DOT=0`.
                assert!(
                    err / want[r].abs().max(1.0) < 5e-5 || err < 1e-3,
                    "gemv row {r}: NEON 8x8 {} vs scalar {}",
                    got[r],
                    want[r]
                );
            }
        }

        if !std::arch::is_aarch64_feature_detected!("i8mm") {
            return;
        }
        for na in 1..=Q8K_ACTS_X4_NC {
            let acts = synth_q8_k_acts(na, cols);
            let tile = prepare_q8_k_acts_x4(&acts, cols);
            for group in 0..n_groups {
                let mut x4_out = vec![0f32; Q6_KX8_NROWS * na];
                gemm_q6_kx8_group_x4(&packed, group, &tile, cols, 8, &mut x4_out);

                let mut group_out = vec![0f32; Q6_KX8_NROWS * na];
                gemm_q6_kx8_group(&packed, group, &acts, cols, 8, &mut group_out);
                assert_eq!(
                    x4_out.iter().map(|v| v.to_bits()).collect::<Vec<_>>(),
                    group_out.iter().map(|v| v.to_bits()).collect::<Vec<_>>(),
                    "x4 entry diverged from the compat entry, group {group} na {na}"
                );

                let nb = cols / Q6_K_BLOCK_ELEMS;
                let slice = &packed[group * nb * Q6_KX8_BLOCK_BYTES..][..nb * Q6_KX8_BLOCK_BYTES];
                let mut want = vec![0f32; Q6_KX8_NROWS * na];
                gemm_q6_kx8_acts_x4_scalar_8(slice, &tile, cols, &mut want);
                for (got, want) in x4_out.iter().zip(want.iter()) {
                    let err = (got - want).abs();
                    // Same 5e-5 as the GEMV check above, for the same
                    // reason: i8mm folds the f32 scales in a different
                    // order than the portable path, and the worst
                    // deviation measured on an i8mm host is 2.6e-5.
                    assert!(
                        err / want.abs().max(1.0) < 5e-5 || err < 1e-3,
                        "group {group} na {na}: i8mm GEMM {got} vs portable {want}"
                    );
                }
            }
        }
    }

    fn synth_q8_0_acts(n: usize, cols: usize) -> Vec<Q8Activations> {
        (0..n)
            .map(|j| {
                let x: Vec<f32> = (0..cols)
                    .map(|i| (((i + j * 13) as f32) * 0.021 - 0.9).sin() * 1.7)
                    .collect();
                quantize_activations_q8(&x)
            })
            .collect()
    }

    /// llama.cpp `ggml_quantize_mat_q8_0_4x8`'s qs ordering, as the
    /// reference `prepare_q8_acts_x4` must reproduce.
    #[test]
    fn prepare_q8_acts_x4_matches_interleave_reference() {
        let n_blocks = 3;
        let cols = n_blocks * Q8_0_BLOCK_ELEMS;
        for na in 1..=Q8K_ACTS_X4_NC {
            let acts = synth_q8_0_acts(na, cols);
            let tile = prepare_q8_acts_x4(&acts, cols);
            assert_eq!(tile.na, na);
            assert_eq!(tile.n_blocks, n_blocks);
            for b in 0..n_blocks {
                for (j, got) in tile.qs[b * 128..(b + 1) * 128].iter().enumerate() {
                    let src_offset = (j / 32) * 8 + (j % 8);
                    let src_id = (j % 32) / 8;
                    let want = if src_id < na {
                        acts[src_id].q[b * Q8_0_BLOCK_ELEMS + src_offset]
                    } else {
                        0
                    };
                    assert_eq!(*got, want, "qs mismatch, block {b} pos {j} na {na}");
                }
                for a in 0..4 {
                    let want_d = acts.get(a).map_or(0.0, |act| act.d[b]);
                    assert_eq!(tile.d[b * 4 + a], want_d, "d mismatch, block {b} row {a}");
                }
            }
        }
    }

    #[test]
    fn q8_0x4_gemm_x4_portable_is_bit_exact_vs_scalar_gemv() {
        let n_blocks = 3;
        let cols = n_blocks * Q8_0_BLOCK_ELEMS;
        let rows = Q8_0X4_NROWS;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q8_0_row(n_blocks, (r * 7 + 3) as u8));
        }
        let packed = pack_q8_0_matrix_x4(&matrix, rows, cols, 8);

        for na in 1..=Q8K_ACTS_X4_NC {
            let acts = synth_q8_0_acts(na, cols);
            let tile = prepare_q8_acts_x4(&acts, cols);
            let mut got = vec![0f32; Q8_0X4_NROWS * na];
            gemm_q8_0x4_acts_x4_scalar_8(&packed, &tile, cols, &mut got);

            for (j, act) in acts.iter().enumerate() {
                let mut want = [0f32; Q8_0X4_NROWS];
                gemv_q8_0x4_q8_0_scalar(&packed, act, cols, 1, 8, &mut want);
                for r in 0..Q8_0X4_NROWS {
                    assert_eq!(
                        got[r * na + j].to_bits(),
                        want[r].to_bits(),
                        "row {r} act {j} na {na}: x4 {} vs GEMV {}",
                        got[r * na + j],
                        want[r]
                    );
                }
            }
        }
    }

    #[test]
    fn q4_0x4_gemm_x4_portable_is_bit_exact_vs_scalar_gemv() {
        let n_blocks = 3;
        let cols = n_blocks * Q4_0_BLOCK_ELEMS;
        let rows = Q4_0X4_NROWS;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q4_0_row(n_blocks, (r * 5 + 1) as u8));
        }
        let packed = pack_q4_0_matrix_x4(&matrix, rows, cols, 8);

        for na in 1..=Q8K_ACTS_X4_NC {
            let acts = synth_q8_0_acts(na, cols);
            let tile = prepare_q8_acts_x4(&acts, cols);
            let mut got = vec![0f32; Q4_0X4_NROWS * na];
            gemm_q4_0x4_acts_x4_scalar_8(&packed, &tile, cols, &mut got);

            for (j, act) in acts.iter().enumerate() {
                let mut want = [0f32; Q4_0X4_NROWS];
                gemv_q4_0x4_q8_0_scalar(&packed, act, cols, 1, 8, &mut want);
                for r in 0..Q4_0X4_NROWS {
                    assert_eq!(
                        got[r * na + j].to_bits(),
                        want[r].to_bits(),
                        "row {r} act {j} na {na}: x4 {} vs GEMV {}",
                        got[r * na + j],
                        want[r]
                    );
                }
            }
        }
    }

    /// The interleave-8 NEON paths (DotProd `4x8` GEMV, i8mm GEMM) against
    /// the scalar interleave-8 references, plus the x4 entries against the
    /// compat entries (bit-exact -- they share the kernels).
    #[test]
    #[cfg(target_arch = "aarch64")]
    fn q8_0_q4_0_interleave8_neon_matches_references_when_available() {
        if !std::arch::is_aarch64_feature_detected!("dotprod") {
            return;
        }
        let n_blocks = 3;
        let n_groups = 2;

        // Q8_0
        let cols = n_blocks * Q8_0_BLOCK_ELEMS;
        let rows = n_groups * Q8_0X4_NROWS;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q8_0_row(n_blocks, (r * 3 + 2) as u8));
        }
        let packed = pack_q8_0_matrix_x4(&matrix, rows, cols, 8);
        let acts = synth_q8_0_acts(4, cols);
        for act in &acts {
            let mut got = vec![0f32; rows];
            gemv_q8_0x4_q8_0(&packed, act, cols, n_groups, 8, &mut got);
            let mut want = vec![0f32; rows];
            gemv_q8_0x4_q8_0_scalar(&packed, act, cols, n_groups, 8, &mut want);
            for r in 0..rows {
                let err = (got[r] - want[r]).abs();
                assert!(
                    err / want[r].abs().max(1.0) < 1e-5 || err < 1e-3,
                    "q8_0 gemv row {r}: NEON 4x8 {} vs scalar {}",
                    got[r],
                    want[r]
                );
            }
        }
        // Q4_0
        let q4_cols = n_blocks * Q4_0_BLOCK_ELEMS;
        let q4_rows = n_groups * Q4_0X4_NROWS;
        let mut q4_matrix = Vec::new();
        for r in 0..q4_rows {
            q4_matrix.extend_from_slice(&synth_q4_0_row(n_blocks, (r * 9 + 1) as u8));
        }
        let q4_packed = pack_q4_0_matrix_x4(&q4_matrix, q4_rows, q4_cols, 8);
        let q4_acts = synth_q8_0_acts(4, q4_cols);
        for act in &q4_acts {
            let mut got = vec![0f32; q4_rows];
            gemv_q4_0x4_q8_0(&q4_packed, act, q4_cols, n_groups, 8, &mut got);
            let mut want = vec![0f32; q4_rows];
            gemv_q4_0x4_q8_0_scalar(&q4_packed, act, q4_cols, n_groups, 8, &mut want);
            for r in 0..q4_rows {
                let err = (got[r] - want[r]).abs();
                assert!(
                    err / want[r].abs().max(1.0) < 1e-5 || err < 1e-3,
                    "q4_0 gemv row {r}: NEON 4x8 {} vs scalar {}",
                    got[r],
                    want[r]
                );
            }
        }

        if !std::arch::is_aarch64_feature_detected!("i8mm") {
            return;
        }
        for na in 1..=Q8K_ACTS_X4_NC {
            let acts = synth_q8_0_acts(na, cols);
            let tile = prepare_q8_acts_x4(&acts, cols);
            for group in 0..n_groups {
                let mut x4_out = vec![0f32; Q8_0X4_NROWS * na];
                gemm_q8_0x4_group_x4(&packed, group, &tile, cols, 8, &mut x4_out);

                let mut group_out = vec![0f32; Q8_0X4_NROWS * na];
                gemm_q8_0x4_group(&packed, group, &acts, cols, 8, &mut group_out);
                assert_eq!(
                    x4_out.iter().map(|v| v.to_bits()).collect::<Vec<_>>(),
                    group_out.iter().map(|v| v.to_bits()).collect::<Vec<_>>(),
                    "q8_0 x4 entry diverged from the compat entry, group {group} na {na}"
                );

                let slice = &packed[group * n_blocks * Q8_0X4_BLOCK_BYTES..]
                    [..n_blocks * Q8_0X4_BLOCK_BYTES];
                let mut want = vec![0f32; Q8_0X4_NROWS * na];
                gemm_q8_0x4_acts_x4_scalar_8(slice, &tile, cols, &mut want);
                for (got, want) in x4_out.iter().zip(want.iter()) {
                    let err = (got - want).abs();
                    assert!(
                        err / want.abs().max(1.0) < 1e-5 || err < 1e-3,
                        "q8_0 group {group} na {na}: i8mm GEMM {got} vs portable {want}"
                    );
                }
            }

            let q4_acts = synth_q8_0_acts(na, q4_cols);
            let q4_tile = prepare_q8_acts_x4(&q4_acts, q4_cols);
            for group in 0..n_groups {
                let mut x4_out = vec![0f32; Q4_0X4_NROWS * na];
                gemm_q4_0x4_group_x4(&q4_packed, group, &q4_tile, q4_cols, 8, &mut x4_out);

                let mut group_out = vec![0f32; Q4_0X4_NROWS * na];
                gemm_q4_0x4_group(&q4_packed, group, &q4_acts, q4_cols, 8, &mut group_out);
                assert_eq!(
                    x4_out.iter().map(|v| v.to_bits()).collect::<Vec<_>>(),
                    group_out.iter().map(|v| v.to_bits()).collect::<Vec<_>>(),
                    "q4_0 x4 entry diverged from the compat entry, group {group} na {na}"
                );

                let slice = &q4_packed[group * n_blocks * Q4_0X4_BLOCK_BYTES..]
                    [..n_blocks * Q4_0X4_BLOCK_BYTES];
                let mut want = vec![0f32; Q4_0X4_NROWS * na];
                gemm_q4_0x4_acts_x4_scalar_8(slice, &q4_tile, q4_cols, &mut want);
                for (got, want) in x4_out.iter().zip(want.iter()) {
                    let err = (got - want).abs();
                    assert!(
                        err / want.abs().max(1.0) < 1e-5 || err < 1e-3,
                        "q4_0 group {group} na {na}: i8mm GEMM {got} vs portable {want}"
                    );
                }
            }
        }
    }

    #[test]
    fn q4_kx8_gemm_with_no_activations_is_a_no_op() {
        let n_blocks = 2;
        let cols = n_blocks * Q4_K_BLOCK_ELEMS;
        let mut matrix = Vec::new();
        for r in 0..Q4_KX8_NROWS {
            matrix.extend_from_slice(&synth_q4_k_row(n_blocks, r as u8));
        }
        let packed = pack_q4_k_matrix_x8(&matrix, Q4_KX8_NROWS, cols, 4);
        let mut out: Vec<f32> = Vec::new();
        gemm_q4_kx8_group(&packed, 0, &[], cols, 4, &mut out);
        assert!(out.is_empty());
    }

    #[test]
    fn q8_0x4_gemm_with_no_activations_is_a_no_op() {
        let n_blocks = 2;
        let cols = n_blocks * Q8_0_BLOCK_ELEMS;
        let mut matrix = Vec::new();
        for r in 0..Q8_0X4_NROWS {
            matrix.extend_from_slice(&synth_q8_0_row(n_blocks, r as u8));
        }
        let packed = pack_q8_0_matrix_x4(&matrix, Q8_0X4_NROWS, cols, Q8_0X4_INTERLEAVE);
        let mut out: Vec<f32> = Vec::new();
        gemm_q8_0x4_group(&packed, 0, &[], cols, Q8_0X4_INTERLEAVE, &mut out);
        assert!(out.is_empty());
    }

    #[test]
    fn q5_kx8_pack_and_gemv_matches_scalar_row_dots() {
        let n_blocks = 2;
        let cols = n_blocks * Q5_K_BLOCK_ELEMS;
        let rows = 16;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q5_k_row(n_blocks, r as u8));
        }
        let x: Vec<f32> = (0..cols)
            .map(|i| ((i as f32) * 0.019 - 1.8).sin() * 1.6)
            .collect();
        let act = quantize_activations_q8_k(&x);

        let row_bytes = n_blocks * Q5_K_BLOCK_BYTES;
        let mut reference = vec![0f32; rows];
        for r in 0..rows {
            reference[r] = dot_q5_k_q8_scalar(&matrix[r * row_bytes..(r + 1) * row_bytes], &act);
        }

        for &interleave in &[4usize, 8] {
            let packed = pack_q5_k_matrix_x8(&matrix, rows, cols, interleave);
            let n_groups = rows / Q5_KX8_NROWS;
            let mut out = vec![0f32; rows];
            gemv_q5_kx8_q8_k(&packed, &act, cols, n_groups, interleave, &mut out);
            for r in 0..rows {
                let err = (out[r] - reference[r]).abs();
                let scale = reference[r].abs().max(1.0);
                assert!(
                    err / scale < 1e-4 || err < 1e-3,
                    "interleave={interleave} row {r}: got {} want {} err={err}",
                    out[r],
                    reference[r]
                );
            }
        }
    }

    #[test]
    fn q5_kx8_gemm_matches_the_gemv_run_once_per_activation() {
        let n_blocks = 3;
        let cols = n_blocks * Q5_K_BLOCK_ELEMS;
        let rows = 2 * Q5_KX8_NROWS;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q5_k_row(n_blocks, (r * 5 + 3) as u8));
        }
        let interleave = q5_kx8_interleave();
        let packed = pack_q5_k_matrix_x8(&matrix, rows, cols, interleave);

        let n_acts = 6;
        let acts: Vec<Q8KActivations> = (0..n_acts)
            .map(|j| {
                let x: Vec<f32> = (0..cols)
                    .map(|i| (((i + j * 29) as f32) * 0.011 - 0.4).cos() * 2.3)
                    .collect();
                quantize_activations_q8_k(&x)
            })
            .collect();

        let row_bytes = n_blocks * Q5_K_BLOCK_BYTES;
        for group in 0..rows / Q5_KX8_NROWS {
            for chunk in acts.chunks(Q5_KX8_GEMM_NC) {
                let mut gemm_out = vec![0f32; Q5_KX8_NROWS * chunk.len()];
                gemm_q5_kx8_group(&packed, group, chunk, cols, interleave, &mut gemm_out);

                for (j, act) in chunk.iter().enumerate() {
                    let mut gemv_out = [0f32; Q5_KX8_NROWS];
                    gemv_q5_kx8_group(&packed, group, act, cols, interleave, &mut gemv_out);
                    for r in 0..Q5_KX8_NROWS {
                        let got = gemm_out[r * chunk.len() + j];
                        let want = gemv_out[r];
                        // Tolerance, not bit equality: on i8mm hosts the
                        // GEMM (i8mm, per-block f32 accumulation) and the
                        // GEMV (DotProd, per-sub-block) round differently.
                        // Measured on an M2 Pro: worst observed relative
                        // deviation 2.9e-5, everything else <= 4.8e-6.
                        let err = (got - want).abs();
                        let scale = want.abs().max(1.0);
                        assert!(
                            err / scale < 5e-5 || err < 1e-3,
                            "group {group} row {r} act {j}: Q5_K GEMM {got} vs GEMV {want}"
                        );
                    }
                }
            }

            // Also check against per-row dot_q5_k_q8 for each activation.
            for (j, act) in acts.iter().enumerate() {
                for r in 0..Q5_KX8_NROWS {
                    let row_idx = group * Q5_KX8_NROWS + r;
                    let row = &matrix[row_idx * row_bytes..(row_idx + 1) * row_bytes];
                    let want = dot_q5_k_q8_scalar(row, act);
                    let mut gemv_out = [0f32; Q5_KX8_NROWS];
                    gemv_q5_kx8_group(&packed, group, act, cols, interleave, &mut gemv_out);
                    let err = (gemv_out[r] - want).abs();
                    let scale = want.abs().max(1.0);
                    assert!(
                        err / scale < 1e-4 || err < 1e-3,
                        "group {group} row {r} act {j}: packed gemv {} vs dot {want}",
                        gemv_out[r]
                    );
                }
            }
        }
    }

    #[test]
    fn q5_kx8_gemm_with_no_activations_is_a_no_op() {
        let n_blocks = 2;
        let cols = n_blocks * Q5_K_BLOCK_ELEMS;
        let mut matrix = Vec::new();
        for r in 0..Q5_KX8_NROWS {
            matrix.extend_from_slice(&synth_q5_k_row(n_blocks, r as u8));
        }
        let packed = pack_q5_k_matrix_x8(&matrix, Q5_KX8_NROWS, cols, 4);
        let mut out: Vec<f32> = Vec::new();
        gemm_q5_kx8_group(&packed, 0, &[], cols, 4, &mut out);
        assert!(out.is_empty());
    }

    #[test]
    fn q6_kx8_pack_and_gemv_matches_scalar_row_dots() {
        let n_blocks = 3;
        let cols = n_blocks * Q6_K_BLOCK_ELEMS;
        let rows = 2 * Q6_KX8_NROWS;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q6_k_row(n_blocks, (r * 5 + 1) as u8));
        }
        let x: Vec<f32> = (0..cols)
            .map(|i| ((i as f32) * 0.017 - 0.8).cos() * 1.8)
            .collect();
        let act = quantize_activations_q8_k(&x);
        let row_bytes = n_blocks * Q6_K_BLOCK_BYTES;
        let mut reference = vec![0f32; rows];
        for r in 0..rows {
            reference[r] = dot_q6_k_q8_scalar(&matrix[r * row_bytes..(r + 1) * row_bytes], &act);
        }
        for interleave in [4usize, 8] {
            let packed = pack_q6_k_matrix_x8(&matrix, rows, cols, interleave);
            let n_groups = rows / Q6_KX8_NROWS;
            let mut out = vec![0f32; rows];
            gemv_q6_kx8_q8_k(&packed, &act, cols, n_groups, interleave, &mut out);
            for r in 0..rows {
                let err = (out[r] - reference[r]).abs();
                let scale = reference[r].abs().max(1.0);
                assert!(
                    err / scale < 1e-4 || err < 1e-3,
                    "interleave={interleave} row {r}: got {} want {} err={err}",
                    out[r],
                    reference[r]
                );
            }
        }
    }

    #[test]
    fn q6_kx8_gemm_matches_the_gemv_run_once_per_activation() {
        let n_blocks = 2;
        let cols = n_blocks * Q6_K_BLOCK_ELEMS;
        let rows = 2 * Q6_KX8_NROWS;
        let mut matrix = Vec::new();
        for r in 0..rows {
            matrix.extend_from_slice(&synth_q6_k_row(n_blocks, (r * 3 + 2) as u8));
        }
        let interleave = q6_kx8_interleave();
        let packed = pack_q6_k_matrix_x8(&matrix, rows, cols, interleave);
        let acts: Vec<_> = (0..Q6_KX8_GEMM_NC)
            .map(|j| {
                let x: Vec<f32> = (0..cols)
                    .map(|i| (((i + j * 11) as f32) * 0.015 - 0.7).sin() * 2.0)
                    .collect();
                quantize_activations_q8_k(&x)
            })
            .collect();
        let row_bytes = n_blocks * Q6_K_BLOCK_BYTES;
        for group in 0..rows / Q6_KX8_NROWS {
            for chunk in acts.chunks(Q6_KX8_GEMM_NC) {
                let mut gemm_out = vec![0f32; Q6_KX8_NROWS * chunk.len()];
                gemm_q6_kx8_group(&packed, group, chunk, cols, interleave, &mut gemm_out);
                for (j, act) in chunk.iter().enumerate() {
                    let mut gemv_out = [0f32; Q6_KX8_NROWS];
                    gemv_q6_kx8_group(&packed, group, act, cols, interleave, &mut gemv_out);
                    for r in 0..Q6_KX8_NROWS {
                        let got = gemm_out[r * chunk.len() + j];
                        let want = gemv_out[r];
                        let err = (got - want).abs();
                        let scale = want.abs().max(1.0);
                        assert!(
                            err / scale < 1e-4 || err < 1e-3,
                            "group {group} row {r} act {j}: gemm {got} vs gemv {want}"
                        );
                        let row_idx = group * Q6_KX8_NROWS + r;
                        let row = &matrix[row_idx * row_bytes..(row_idx + 1) * row_bytes];
                        let dot = dot_q6_k_q8_scalar(row, act);
                        let err2 = (got - dot).abs();
                        let scale2 = dot.abs().max(1.0);
                        assert!(
                            err2 / scale2 < 1e-4 || err2 < 1e-3,
                            "group {group} row {r} act {j}: gemm {got} vs dot {dot}"
                        );
                    }
                }
            }
        }
    }

    #[test]
    fn block_size_matches_ggml() {
        assert_eq!(Q4_KX8_BLOCK_BYTES, 16 + 16 + 96 + 1024);
        assert_eq!(Q5_KX8_BLOCK_BYTES, 16 + 16 + 96 + 256 + 1024);
        assert_eq!(Q6_KX8_BLOCK_BYTES, 16 + 128 + 1024 + 512);
        assert_eq!(Q8_0X4_BLOCK_BYTES, 4 * 2 + Q8_0_BLOCK_ELEMS * Q8_0X4_NROWS);
        assert_eq!(Q4_0X4_BLOCK_BYTES, 4 * 2 + Q4_0_BLOCK_ELEMS * 2);
    }
}