# MPS (Apple Silicon) Install FastVideo on Apple Silicon and run FastMetal-QAD. Apple Silicon uses the MLX runtime and the FastMetal-QAD INT8 checkpoints. See the [FastMetal-QAD blog](https://haoailab.com/blogs/fastmetal/) and the [FastMetal collection](https://huggingface.co/collections/FastVideo/fastmetal). ## Requirements - **OS: macOS 14 or newer** - **Python: 3.12.4** ## Set up using Python ### Create a new Python environment #### uv Recommended default: use [uv](https://docs.astral.sh/uv/) for faster and more stable environment setup. Please follow the [documentation](https://docs.astral.sh/uv/#getting-started) to install `uv`. After installing `uv`, create a new environment using: ```console # (Recommended) Create a new uv environment. Use `--seed` to install `pip` and `setuptools`. uv venv --python 3.12 --seed source .venv/bin/activate ``` #### Conda (alternative) You can also create a Python environment using [Conda](https://docs.conda.io/projects/conda/en/stable/user-guide/getting-started.html). ##### 1. Install Miniconda (if not already installed) ```bash wget https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-arm64.sh bash Miniconda3-latest-MacOSX-arm64.sh source ~/.zshrc ``` ##### 2. Create and activate a Conda environment for FastVideo ```bash conda create -n fastvideo python=3.12.4 -y conda activate fastvideo ``` ### Dependencies ``` brew install ffmpeg ``` ### Installation FastMetal's native Apple Silicon runtime requires the `mlx` extra. #### With uv (recommended) ```bash uv pip install "fastvideo[mlx]" ``` #### With Conda environment (alternative) `uv` works inside an active conda env too, so prefer `uv pip` for the actual install: ```bash uv pip install "fastvideo[mlx]" ``` ### Installation from Source #### 1. Clone the FastVideo repository ```bash git clone https://github.com/hao-ai-lab/FastVideo.git && cd FastVideo ``` #### 2. Install FastVideo Basic installation: ```bash uv pip install -e ".[mlx]" ``` Alternative with Conda environment: ```bash uv pip install -e ".[mlx]" ``` ## Run FastMetal-QAD Each release is self-contained. Download one checkpoint and point both `--model-root` and `--mlx-checkpoint` at it (the example also auto-detects `mlx_dit.json` under `--model-root`). | Checkpoint | Script | Mac tier | | --- | --- | --- | | [`FastVideo/FastMetal-1.3B-QAD`](https://huggingface.co/FastVideo/FastMetal-1.3B-QAD) | `mlx_wan_prompt_to_video.py` | 16 GB+ | | [`FastVideo/FastMetal-5B-QAD`](https://huggingface.co/FastVideo/FastMetal-5B-QAD) | `mlx_wan22_generate.py` | 16 GB+ | | [`FastVideo/FastMetal-14B-QAD`](https://huggingface.co/FastVideo/FastMetal-14B-QAD) | `mlx_wan_prompt_to_video.py` | 36 GB+ | ```bash hf download FastVideo/FastMetal-1.3B-QAD --local-dir ./FastMetal-1.3B-QAD python examples/inference/basic/mlx_wan_prompt_to_video.py \ --model-root ./FastMetal-1.3B-QAD \ --mlx-checkpoint ./FastMetal-1.3B-QAD \ --height 480 --width 832 --num-frames 81 \ --prompt "A bird's-eye view of a misty forest valley at dawn." ``` 14B uses the same script. Point both flags at `./FastMetal-14B-QAD`. That repo also ships an EMA variant: keep `--model-root` at the repo root and set `--mlx-checkpoint ./FastMetal-14B-QAD/ema`. Wan2.2 5B uses a different latent layout, so it has its own entrypoint: ```bash hf download FastVideo/FastMetal-5B-QAD --local-dir ./FastMetal-5B-QAD python examples/inference/basic/mlx_wan22_generate.py \ --mlx-checkpoint ./FastMetal-5B-QAD \ --text-encoder-root ./FastMetal-5B-QAD \ --vae-root ./FastMetal-5B-QAD/vae \ --height 704 --width 1280 --num-frames 81 \ --prompt "A cinematic portrait with soft neon lighting and smooth camera motion." ``` CUDA FastWan-QAD (`FastVideo/FastWan-QAD-1.3B`, `FastVideo/FastWan-QAD-FP8-1.3B`) is a separate NVIDIA release. The MLX examples look for FastMetal packed weights (`mlx_dit.json`). `basic_mps.py` is a generic PyTorch MPS demo. For local video on Mac, use the FastMetal commands above. ## Development Environment Setup If you're planning to contribute to FastVideo please see the following page: [Contributor Guide](../../contributing/overview.md) ## Hardware Requirements - **1.3B / 5B:** 16 GB unified memory and up (M1 and later) - **14B:** 36 GB unified memory and up - Fanless 13-inch MacBook Air can run 1.3B and 5B at the same resolutions ## Troubleshooting If you encounter any issues during installation, please open an issue on our [GitHub repository](https://github.com/hao-ai-lab/FastVideo). You can also join our [Slack community](https://join.slack.com/t/fastvideo/shared_invite/zt-3f4lao1uq-u~Ipx6Lt4J27AlD2y~IdLQ) for additional support.