mold

Generate images and short video clips on your own GPU. No cloud, no Python, no fuss.

Documentation | Getting Started | Models | API

mold run "a cat riding a motorcycle through neon-lit streets"

That's it. Mold auto-downloads the model on first run and saves the image to your current directory.

Install

curl -fsSL https://raw.githubusercontent.com/utensils/mold/main/install.sh | sh

This downloads the latest tagged release from releases/latest and installs it to ~/.local/bin/mold. On Linux, the installer auto-detects your NVIDIA GPU and picks the right binary (RTX 40-series or RTX 50-series). macOS builds include Metal support.

Pin a specific version with MOLD_VERSION:

curl -fsSL https://raw.githubusercontent.com/utensils/mold/main/install.sh | MOLD_VERSION=v0.10.0 sh

Nix

nix run github:utensils/mold -- run "a cat"                   # Ada / RTX 40-series
nix run github:utensils/mold#mold-sm120 -- run "a cat"        # Blackwell / RTX 50-series

AUR — Arch Linux

paru -S mold-ai-bin     # Prebuilt binary, CUDA sm_89 (RTX 40-series). Fastest.
paru -S mold-ai         # Builds from source — set CUDA_COMPUTE_CAP=120 for RTX 50-series
paru -S mold-ai-git     # Builds from main HEAD

Conflicts with extra/mold (the rui314 linker) — they share the /usr/bin/mold path. See packaging/aur/README.md for details and the Blackwell (sm_120) build flag.

From source

./scripts/ensure-web-dist.sh && cargo build --profile dev-fast -p mold-ai --features cuda   # Linux (NVIDIA), fast local build
./scripts/ensure-web-dist.sh && cargo build --profile dev-fast -p mold-ai --features metal  # macOS (Apple Silicon), fast local build
cargo build --release -p mold-ai --features cuda                                          # Linux (NVIDIA), shipping build
cargo build --release -p mold-ai --features metal                                         # macOS (Apple Silicon), shipping build

Add preview, expand, discord, or tui to the features list as needed.

Manual download

Pre-built binaries on the releases page.

Desktop app

Mold also has a native desktop app for macOS and Linux. It brings Generate, Gallery, Models, Chains, History, Jobs, RunPod, and Settings into one interface, and can use this device alongside multiple remote Mold hosts. The unified Catalog keeps installed models above the live catalog with image/video filters and pinned downloads, and lets you choose which host receives a download. Its Installed shelf merges every connected host with host badges, while both that screen and each host detail page show host-scoped pull progress. Size labels separate checkpoint weights from the larger footprint including shared runtime components. Curated built-in variants take precedence over ambiguous multi-checkpoint Hugging Face repositories, so a pull targets one runnable model instead of an entire aggregate repository. Every remembered remote host is retried immediately whenever the app launches, independently of This Mac's startup; unreachable hosts stay visible and retry. Chains also uses the all-host video-model union and keeps creation, progress, previews, and durable job actions routed to the selected model's host.

Download Mold for macOS · Desktop guide

The macOS DMG is signed and notarized. Linux builds are currently available through Nix or as source/CI artifacts; tagged releases do not publish an AppImage yet. Detailed setup, multi-host behavior, and update-channel guidance live in the desktop guide.

Usage

mold run "a sunset over mountains"                    # Generate with default model
mold run flux-dev:q4 "a turtle in the desert"         # Pick a model
mold run "a portrait" --width 768 --height 1024       # Custom size
mold run "a sunset" --batch 4 --seed 42               # Batch with reproducible seeds
mold run "oil painting" --image photo.png              # img2img
mold run qwen-image-edit-2511:q4 "make the chair red leather" --image chair.png --image swatch.png
mold run ltx-video-0.9.6-distilled:bf16 "a fox in the snow" --frames 25
mold run "a cat" --expand                              # LLM prompt expansion
mold run qwen-image:q2 "a poster" --qwen2-variant q6  # Qwen-Image quantized text encoder
mold run flux-dev:bf16 "portrait" --lora style.safetensors  # LoRA adapter

Inline preview

Display generated images directly in the terminal (requires preview feature):

mold run "a cat" --preview

Piping

mold run "neon cityscape" | viu -                     # Pipe to image viewer
echo "a cat" | mold run flux-schnell                  # Pipe prompt from stdin

Terminal UI

mold tui

Model management

mold list                    # See what you have
mold pull flux-dev:q4        # Download a model
mold rm dreamshaper-v8       # Remove a model
mold stats                   # Disk usage overview
mold clean                   # Clean orphaned files (dry-run)
mold clean --force           # Actually delete

Remote rendering

# On your GPU server
mold serve

# From your laptop
MOLD_HOST=http://gpu-server:7680 mold run "a cat"

Cloud GPU via mold runpod

Generate on a cloud GPU without managing pods yourself:

mold config set runpod.api_key <key>         # one-time setup
mold runpod run "a cat on a skateboard"       # creates pod → generates → saves to ./mold-outputs/
mold runpod network-volume create --name models --size 100 --dc US-KS-2
mold runpod run "a cat" --network-volume <volume-id>

mold runpod run selects an available GPU, streams progress, and keeps the pod warm for reuse. See the RunPod CLI guide for provisioning, storage, diagnostics, and lifecycle commands.

See the full CLI reference, configuration guide, and model catalog in the documentation.

Models

Supports 11 model families with 80+ variants:

Bare names auto-resolve: mold run flux-schnell "a cat" picks the best available variant.

See the full model catalog for sizes, VRAM requirements, and recommended settings.

Features

• txt2img, img2img, multimodal edit, inpainting — full generation pipeline
• Image upscaling — Real-ESRGAN super-resolution (2x/4x) via mold upscale, server API, or TUI; first use auto-downloads the upscaler on the host running the job, and post-generation upscale retains both original and upscaled gallery artifacts
• LoRA adapters — FLUX, Flux.2, LTX-2, SD1.5, SD3/SD3.5, SDXL, Qwen-Image, Qwen-Image-Edit, and Z-Image
• ControlNet — canny, depth, openpose (SD1.5)
• Prompt expansion — local LLM (Qwen3-1.7B) enriches short prompts
• Negative prompts — CFG-based models (SD1.5, SDXL, SD3, Wuerstchen)
• Pipe-friendly — echo "a cat" | mold run | viu -
• PNG metadata — embedded prompt, seed, model info
• Terminal preview — Kitty, Sixel, iTerm2, halfblock
• Smart VRAM — quantized encoders, block offloading, drop-and-reload
• Qwen family encoder control — selectable Qwen2.5-VL variants for Qwen-Image and Qwen-Image-Edit, with quantized auto-fallback when BF16 would be too heavy
• Shell completions — bash, zsh, fish, elvish, powershell
• REST API — mold serve with SSE streaming, auth, rate limiting
• Discord bot — slash commands with role permissions and quotas
• Interactive TUI — generate, gallery, models, settings
• Native desktop — local and multi-host generation, gallery, model library, chains, history, jobs, RunPod, and settings

Deployment

How it works

Single Rust binary built on candle for the in-tree model families. LTX-2 now runs through the native Rust stack in mold-inference, so the full model surface stays in Rust with no libtorch dependency.

mold run "a cat"
  │
  ├─ Server running? → send request over HTTP
  │
  └─ No server? → load model locally on GPU
       ├─ Encode prompt (T5/CLIP text encoders)
       ├─ Denoise latent (transformer/UNet)
       ├─ Decode pixels (VAE)
       └─ Save PNG

Requirements

• NVIDIA GPU with CUDA or Apple Silicon with Metal
• Models auto-download on first use (~2-30GB depending on model)