---
license: apache-2.0
---
---
license: apache-2.0
---

# FastVideo FastWan2.1-T2V-14B-480P-Diffusers
<p align="center">
  <img src="https://raw.githubusercontent.com/hao-ai-lab/FastVideo/main/assets/logo.jpg" width="200"/>
</p>
<div>
  <div align="center">
    <a href="https://github.com/hao-ai-lab/FastVideo" target="_blank">FastVideo Team</a>&emsp;
  </div>

  <div align="center">
    <a href="https://arxiv.org/pdf/2505.13389">Paper</a> | 
    <a href="https://github.com/hao-ai-lab/FastVideo">Github</a>
  </div>
</div>



## Model Overview
- This model is jointly finetuned with [DMD](https://arxiv.org/pdf/2405.14867) and [VSA](https://arxiv.org/pdf/2505.13389), based on [Wan-AI/Wan2.1-T2V-14B-Diffusers](https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B-Diffusers).  
- It supports 3-step inference and achieves up to 50x speed up.  
- Both [finetuning](https://github.com/hao-ai-lab/FastVideo/blob/main/scripts/distill/v1_distill_dmd_wan_VSA.sh) and [inference](https://github.com/hao-ai-lab/FastVideo/blob/main/scripts/inference/v1_inference_wan_dmd.sh) scripts are available in the [FastVideo](https://github.com/hao-ai-lab/FastVideo) repository.  
- Try it out on **FastVideo** — we support a wide range of GPUs from **H100** to **4090**, and even support **Mac** users!
- We use [FastVideo 480P Synthetic Wan dataset](https://huggingface.co/datasets/FastVideo/Wan-Syn_77x448x832_600k) for training.



If you use FastWan2.1-T2V-14B-480P-Diffusers model for your research, please cite our paper:
```
@article{zhang2025vsa,
  title={VSA: Faster Video Diffusion with Trainable Sparse Attention},
  author={Zhang, Peiyuan and Huang, Haofeng and Chen, Yongqi and Lin, Will and Liu, Zhengzhong and Stoica, Ion and Xing, Eric and Zhang, Hao},
  journal={arXiv preprint arXiv:2505.13389},
  year={2025}
}
@article{zhang2025fast,
  title={Fast video generation with sliding tile attention},
  author={Zhang, Peiyuan and Chen, Yongqi and Su, Runlong and Ding, Hangliang and Stoica, Ion and Liu, Zhengzhong and Zhang, Hao},
  journal={arXiv preprint arXiv:2502.04507},
  year={2025}
}
```