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license: other
license_name: ltx-video-license
license_link: https://huggingface.co/Lightricks/LTX-2/blob/main/LICENSE.md
library_name: mlx
tags:
- video-generation
- mlx
- apple-silicon
- ltx-2
- dev
- quantized
---
# LTX-2 19B Dev (4-bit) - MLX
This is a 4-bit quantized version of the [LTX-2 19B Dev](https://huggingface.co/Lightricks/LTX-2) model, optimized for Apple Silicon using MLX.
## Model Description
LTX-2 is a state-of-the-art video generation model from Lightricks. This version has been quantized to 4-bit precision for efficient inference on Apple Silicon devices with MLX.
### Key Features
- **Pipeline**: Dev (full control with CFG scale)
- **Quantization**: 4-bit precision
- **Framework**: MLX (Apple Silicon optimized)
- **Memory**: ~19GB VRAM required
## Usage
### Installation
```bash
pip install git+https://github.com/CharafChnioune/mlx-video.git
```
### Command Line
```bash
# Basic generation
mlx-video --prompt "A beautiful sunset over the ocean" \
--model-repo AITRADER/ltx2-dev-4bit-mlx \
--pipeline dev \
--height 512 --width 512 \
--num-frames 33
# Dev pipeline with CFG
mlx-video --prompt 'A cat playing with yarn' \\
--model-repo AITRADER/ltx2-dev-4bit-mlx \\
--pipeline dev \\
--steps 40 --cfg-scale 4.0
```
### Python API
```python
from mlx_video import generate_video
video = generate_video(
prompt="A beautiful sunset over the ocean",
model_repo="AITRADER/ltx2-dev-4bit-mlx",
pipeline="dev",
height=512,
width=512,
num_frames=33,
)
```
## Model Files
- `ltx-2-19b-dev-mlx.safetensors` - Main model weights (4-bit quantized)
- `quantization.json` - Quantization configuration
- `config.json` - Model configuration
- `layer_report.json` - Layer information
## Performance
| Resolution | Frames | Steps |
|------------|--------|------|
| 512x512 | 33 | ~40 steps |
| 768x512 | 33 | ~40 steps |
## License
This model is released under the [LTX Video License](https://huggingface.co/Lightricks/LTX-2/blob/main/LICENSE.md).
## Acknowledgements
- [Lightricks](https://lightricks.com/) for the original LTX-2 model
- [MLX](https://github.com/ml-explore/mlx) team at Apple for the framework
- [mlx-video](https://github.com/CharafChnioune/mlx-video) for the MLX conversion
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