Wan 2.1 T2V 14B
π Wan | π₯οΈ GitHub | π€ Hugging Face | π€ ModelScope | π Paper (Coming soon) | π Blog | π¬ WeChat Group | π Discord
Model source
- Kind
- Other
- File size
- 484 MBβ10.6 GB
- Version
- vRevision a064a6c
- Updated
- Sep 14, 2026
- Publisher
- @Wan-AI
- Downloads
- 38.6K
- Parameters
- 14B
- Source
- Hugging Face
Source excerpt
π Wan | π₯οΈ GitHub | π€ Hugging Face | π€ ModelScope | π Paper (Coming soon) | π Blog | π¬ WeChat Group | π Discord
Sources
1 source
Sources
1 sourceVerified Aug 9
Model artifacts
8 artifacts
Model artifacts
8 artifactsdiffusion_pytorch_model-00001-of-00006.safetensors
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safetensors Β· 9.16 GB Β· SHA-256 741fd1508cd0β¦2cea Β· Hugging Face
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safetensors Β· 9.16 GB Β· SHA-256 47b08ba289b1β¦81ba Β· Hugging Face
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pth Β· 10.6 GB Β· SHA-256 7cace0da2b44β¦d81d Β· Hugging Face
DownloadSource excerpts
3 excerpts
Source excerpts
3 excerpts--- license: apache-2.0 language: - en - zh pipeline_tag: text-to-video tags: - video generation library_name: diffusers inference: parameters: num_inference_steps: 10 --- # Wan2.1 <p align="center"> <img src="assets/logo.png" width="400"/> <p> <p align="center"> π <a href=""><b>Wan</b></a>    ο½    π₯οΈ <a href="https://github.com/Wan-Video/Wan2.1">GitHub</a>    |   π€ <a href="https://huggingface.co/Wan-AI/">Hugging Face</a>   |   π€ <a href="https://modelscope.cn/organization/Wan-AI">ModelScope</a>   |    π <a href="">Paper (Coming soon)</a>    |    π <a href="https://wanxai.com">Blog</a>    |   π¬ <a href="https://gw.alicdn.com/imgextra/i2/O1CN01tqjWFi1ByuyehkTSB_!!6000000000015-0-tps-611-1279.jpg">WeChat Group</a>   |    π <a href="https://discord.gg/p5XbdQV7">Discord</a>   <br> ----- [**Wan: Open and Advanced Large-Scale Video Generative Models**]("") <be> In this repository, we present **Wan2.1**, a comprehensive and open suite of video foundation models that pushes the boundaries of video generation. **Wan2.1** offers these key features: - π **SOTA Performance**: **Wan2.1** consistently outperforms existing open-source models and state-of-the-art commercial solutions across multiple benchmarks. - π **Supports Consumer-grade GPUs**: The T2V-1.3B model requires only 8.19 GB VRAM, making it compatible with almost all consumer-grade GPUs. It can generate a 5-second 480P video on an RTX 4090 in about 4 minutes (without optimization techniques like quantization). Its performance is even comparable to some closed-source models. - π **Multiple Tasks**: **Wan2.1** excels in Text-to-Video, Image-to-Video, Video Editing, Text-to-Image, and Video-to-Audio, advancing the field of video generation. - π **Visual Text Generation**: **Wan2.1** is the first video model capable of generating both Chinese and English text, featuring robust text generation that enhances its practical applications. - π **Powerful Video VAE**: **Wan-VAE** delivers exceptional efficiency and performance, encoding and decoding 1080P videos of any length while preserving temporal information, making it an ideal foundation for video and image generation. This repository features our T2V-14B model, which establishes a new SOTA performance benchmark among bo...
Source context: 38642 downloads Β· 1542 likes Β· Pipeline text-to-video Β· Library diffusers Β· Repo Wan-AI/Wan2.1-T2V-14B
Source context: 72168 downloads Β· 1532 likes Β· Pipeline text-to-video Β· Library diffusers Β· Repo Wan-AI/Wan2.1-T2V-14B
