mold

Local AI image and video generation on your own GPU — NVIDIA CUDA and Apple Silicon Metal, no Python, no cloud account, no usage fees. CLI-native and pipe-friendly, with a native desktop app, web studio, TUI, iPhone companion, Discord bot, and REST/SSE API built on the same engine.

Documentation · Models · Desktop guide · API

Install

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

The installer picks the right prebuilt binary for your GPU and verifies its checksum. Nix (nix run github:utensils/mold), Arch (paru -S mold-ai-bin), and source builds are covered in the installation guide; binaries and checksums are on the releases page. GH200, GB200, and GB300 require future linux/arm64 artifacts and are unsupported.

Quick start

# Generate with the default model
mold run "a cat riding a motorcycle through neon-lit streets"

# Choose a model and reproducible seed
mold run flux-dev:q4 "a sunset over mountains" --seed 42

# Edit an image
mold run qwen-image-edit-2511:q4 "make the chair red" --image chair.png

# Generate video
mold run ltx-video-0.9.6-distilled:bf16 "a fox in the snow" --frames 25

# Launch the web studio and API
mold serve

Models download automatically on first use. Generated media is saved locally with prompt, model, seed, and generation metadata.

What it supports

• Models: FLUX.1, Flux.2 Klein/Dev, SD 1.5, SDXL, SD 3.5, Z-Image, Qwen-Image, Qwen-Image-Edit, Wuerstchen v2, LTX Video, LTX-2 / LTX-2.3, Wan 2.1/2.2, and MiniMax H3 — see the model catalog for sizes, VRAM needs, and settings
• Images: text-to-image, img2img, multimodal editing, inpainting, ControlNet, LoRA, prompt expansion, and Real-ESRGAN upscaling
• Video and audio: text/image-to-video, multi-prompt sequences, clip continuation (--extend), lip dub (--pipeline lip-dub), text-to-audio (--pipeline t2a), native MP4 with generated audio, and LTX-2 output up to 4K via tiled composition
• Fits your hardware: quantized variants, encoder fallback, smart VRAM placement, block offloading, and spatial tiling (--spatial-tile)
• Multi-machine: connect LAN/Tailscale hosts and RunPod, route jobs by capability, and browse every machine's gallery in one place

MiniMax H3 weights use the MiniMax H3 Community License, not Mold's MIT license. H3 may be used through Mold in every territory and workflow — local, remote, shared, hosted, output distribution, and redistribution — with no separate acceptance step; review the linked terms for your use. Current capability limits (FL2VA on SM89 CUDA only) are documented in the H3 model guide.

Mold Studio

One native desktop app for macOS and Linux with five workspaces — Create, Library, Models, Machines, and Settings — spanning local and remote generation, a merged multi-machine gallery, model discovery from Hugging Face and Civitai, GPU telemetry, and QR pairing for the iPhone companion.

Download Mold for macOS (Apple Silicon) · Explore the desktop app

More ways to create

Preview generations directly in supported terminals:

mold run "a cat" --preview

Or open the keyboard-first terminal interface with mold tui:

Run the engine where the GPU lives and point any client at it:

mold serve                                      # GPU machine
MOLD_HOST=http://gpu-server:7680 mold run "a cat"  # laptop

See the remote workflow and RunPod guides.

Project

Mold is a Rust workspace built on candle. The documentation covers the CLI, configuration, deployment, and HTTP API.

Core contributors: James Brink and Jeffrey Dilley.

Licensed under the MIT License.