Lynx: High-Fidelity Personalized Video Generation
Shen Sang* Tiancheng Zhi* Tianpei Gu Jing Liu Linjie Luo
Intelligent Creation, ByteDance
* Equal Contribution

Lynx is a state-of-the-art high-fidelity personalized video generation model that creates videos from a single input image while preserving the subject's identity. Built on a Diffusion Transformer (DiT) foundation model with lightweight ID-adapters and Ref-adapters for identity preservation and spatial detail enhancement.
Model Variants
This repository contains two model variants:
- Lynx Full Model (
lynx_full
): Complete version with all advanced features and best performance - Lynx Lite Model (
lynx_lite
): Lightweight model with fewer parameters (no Ref-adapter), tailored for efficient 24fps (121-frame) video generation.
Citation
If you use this model in your research, please cite:
@article{sang2025lynx,
title={Lynx: Towards High-Fidelity Personalized Video Generation},
author={Sang, Shen and Zhi, Tiancheng and Gu, Tianpei and Liu, Jing and Luo, Linjie},
journal={arXiv preprint arXiv:2509.15496},
year={2025}
}
License
This model is licensed under the Apache License 2.0. See the LICENSE file for details.
Model tree for ByteDance/lynx
Base model
Wan-AI/Wan2.1-T2V-14B