[][src]Crate glam


glam is a simple and fast linear algebra library for games and graphics.


glam is built with SIMD in mind. Currently only SSE2 on x86/x86_64 is supported as this is what stable Rust supports.

  • Single precision float (f32) support only
  • SSE2 implementation for most types, including Mat2, Mat3, Mat4, Quat, Vec3 and Vec4
  • Scalar fallback implementations exist when SSE2 is not available
  • Most functionality includes unit tests and benchmarks

Linear algebra conventions

glam interprets vectors as column matrices (also known as "column vectors") meaning when transforming a vector with a matrix the matrix goes on the left.

use glam::{Mat3, Vec3};
let m = Mat3::identity();
let x = Vec3::unit_x();
let v = m * x;
assert_eq!(v, x);

Matrices are stored in memory in column-major order.

Rotations follow left-hand rule. The direction of the axis gives the direction of rotation: with the left thumb pointing in the positive direction of the axis the left fingers curl around the axis in the direction of the rotation.

use glam::{Mat3, Vec3};
// rotate +x 90 degrees clockwise around y giving -z
let m = Mat3::from_rotation_y(90.0_f32.to_radians());
let v = m * Vec3::unit_x();
assert!(v.abs_diff_eq(-Vec3::unit_z(), core::f32::EPSILON));

Size and alignment of types

Most glam types use SIMD for storage meaning most types are 16 byte aligned. The only exception is Vec2`. When SSE2 is not available on the target architecture the types will still be 16 byte aligned, so object sizes and layouts will not change between architectures.

16 byte alignment means that some types will have a stride larger than their size resulting in some wasted space.

Typef32 bytesSIMD bytesWasted bytes

Despite this wasted space the SIMD version tends to outperform the f32 implementation in mathbench benchmarks.

SIMD support can be disabled entirely using the scalar-math feature. This feature will also disable SIMD alignment meaning most types will use native f32 alignment of 4 bytes.

All the main glam types are tagged with #[repr(C)], so they are possible to expose as struct members to C interfaces if desired. Be mindful of Vec3's extra float though.

Accessing internal data

The SIMD types that glam builds on are opaque and their contents are not directly accessible. Because of this glam types uses getter and setter methods instead of providing direct access.

use glam::Vec3;
let mut v = Vec3::new(1.0, 2.0, 3.0);
assert_eq!(v.y(), 2.0);
assert_eq!(v.z(), 1.0);

If you need to access multiple elements it is easier to convert the type to a tuple or array:

use glam::Vec3;
let v = Vec3::new(1.0, 2.0, 3.0);
let (x, y, z) = v.into();
assert_eq!((x, y, z), (1.0, 2.0, 3.0));

SIMD and scalar consistency

glam types implement serde Serialize and Deserialize traits to ensure that they will serialize and deserialize exactly the same whether or not SIMD support is being used.

The SIMD versions implement core::fmt::Display traits so they print the same as the scalar version.

use glam::Vec3;
let a = Vec3::new(1.0, 2.0, 3.0);
assert_eq!(format!("{}", a), "[1, 2, 3]");

Feature gates

All glam dependencies are optional, however some are required for tests and benchmarks.

  • std - the default feature, has no dependencies.
  • rand - used to generate random values. Used in benchmarks.
  • serde - used for serialization and deserialization of types.
  • mint - used for interoperating with other linear algebra libraries.
  • scalar-math - disables SIMD support and uses native alignment for all types.
  • debug-glam-assert - adds assertions in debug builds which check the validity of parameters passed to glam to help catch runtime errors.
  • glam-assert - adds assertions to all builds which check the validity of parameters passed to glam to help catch runtime errors.





A 2x2 column major matrix.


A 3x3 column major matrix.


A 4x4 column major matrix.


A quaternion representing an orientation.


A 2-dimensional vector.


A 2-dimensional vector mask.


A 3-dimensional vector.


A 3-dimensional vector mask.


A 4-dimensional vector.


A 4-dimensional vector mask.