⚡️ LightX2V:
Light Video Generation Inference Framework

[ English | 中文 ]

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LightX2V is a lightweight video generation inference framework designed to provide an inference tool that leverages multiple advanced video generation inference techniques. As a unified inference platform, this framework supports various generation tasks such as text-to-video (T2V) and image-to-video (I2V) across different models. X2V means transforming different input modalities (such as text or images) to video output.

💡 How to Start

Please refer to our documentation: English Docs | 中文文档.

🤖 Supported Model List

• ✅ HunyuanVideo-T2V
• ✅ HunyuanVideo-I2V
• ✅ Wan2.1-T2V
• ✅ Wan2.1-I2V
• ✅ Wan2.1-T2V-StepDistill-CfgDistill (recommended 🚀🚀🚀)
• ✅ Wan2.1-T2V-CausVid
• ✅ SkyReels-V2-DF
• ✅ CogVideoX1.5-5B-T2V

🧾 Contributing Guidelines

We have prepared a pre-commit hook to enforce consistent code formatting across the project.

Tip

• Install the required dependencies:

pip install ruff pre-commit

• Then, run the following command before commit:

pre-commit run --all-files

Thank you for your contributions!

🤝 Acknowledgments

We built the code for this repository by referencing the code repositories involved in all the models mentioned above.

🌟 Star History

✏️ Citation

If you find our framework useful to your research, please kindly cite our work:

@misc{lightx2v,
 author = {lightx2v contributors},
 title = {LightX2V: Light Video Generation Inference Framework},
 year = {2025},
 publisher = {GitHub},
 journal = {GitHub repository},
 howpublished = {\url{https://github.com/ModelTC/lightx2v}},
}