mlx-video

MLX-Video is the best package for inference and finetuning of Image-Video-Audio generation models on your Mac using MLX.

Installation

Option 1: Install with pip (requires git):

pip install git+https://github.com/Blaizzy/mlx-video.git

Option 2: Install with uv (ultra-fast package manager, optional):

uv pip install git+https://github.com/Blaizzy/mlx-video.git

Supported Models

LTX-2

LTX-2 is a 19B parameter video generation model from Lightricks. See the full LTX-2 model card for detailed usage, CLI options, pipeline descriptions, and architecture.

Features:

Text-to-Video (T2V), Image-to-Video (I2V), and Audio-to-Video (A2V)
Four pipelines: Distilled (fast), Dev (CFG), Dev Two-Stage (LoRA), Dev Two-Stage HQ (highest quality)
Synchronized audio-video generation (experimental)
LoRA support (local files or HuggingFace repos)
Prompt enhancement via Gemma
2x spatial upscaling for images and videos

Quick start:

# Text-to-Video (distilled, fastest)
uv run mlx_video.generate --prompt "Two dogs wearing sunglasses, cinematic, sunset" -n 97 --width 768

# Image-to-Video
uv run mlx_video.generate --prompt "A person dancing" --image photo.jpg

# Audio-to-Video
uv run mlx_video.generate --audio-file music.wav --prompt "A band playing music"

# Dev pipeline with CFG (higher quality)
uv run mlx_video.generate --pipeline dev --prompt "A cinematic scene" --cfg-scale 3.0

# Dev two-stage HQ (highest quality)
uv run mlx_video.generate --pipeline dev-two-stage-hq \
    --prompt "A cinematic scene of ocean waves at golden hour" \
    --model-repo prince-canuma/LTX-2-dev

Converting weights:

Pre-converted weights are available on HuggingFace (LTX-2-distilled, LTX-2-dev, LTX-2.3-distilled, LTX-2.3-dev), or convert from the original Lightricks checkpoint:

uv run python -m mlx_video.models.ltx_2.convert \
    --source Lightricks/LTX-2 --output ./LTX-2-distilled --variant distilled

Requirements

macOS with Apple Silicon
Python >= 3.11
MLX >= 0.22.0

License

MIT

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