Wan
Wan is an open suite of video foundation models for generating and editing media.
What Wan is
Wan is an open suite of video foundation models for generating and editing media. It supports text-to-video and image-to-video, along with video editing, text-to-image, and video-to-audio tasks. The models can add Chinese or English text to videos. For editing, VACE can use a text prompt with optional video, mask, and image inputs. Wan runs on Linux and can be self-hosted; it is free, open source under Apache-2.0, and permits commercial use.
The T2V-14B model supports 480P and 720P output, while T2V-1.3B supports 480P; the project cautions that 1.3B results at 720P are less stable. The 1.3B model requires 8.19 GB of VRAM. The project reports about four minutes to generate five seconds of 480P video on an RTX 4090 without quantization. Wan-VAE can encode and decode 1080P videos of any length while preserving temporal information. Model downloads are linked through Hugging Face and ModelScope. Installation guidance covers pip and Poetry and calls for PyTorch 2.4.0 or later. The repository includes command-line and local Gradio examples, and integrations include Diffusers and ComfyUI.
Good
- Free and open source under Apache-2.0
- Supports video, image, and audio generation tasks
- Commercial use is permitted
- Local Gradio and command-line examples are included
Watch out
- T2V-1.3B requires 8.19 GB of VRAM
- T2V-1.3B supports 480P; 720P is less stable
Who it suits
Wan suits Linux users who want to self-host video generation models and need tasks such as text-to-video, image-to-video, or video editing. Its commercial-use permission may also suit commercial projects.
Verdict
Wan offers a range of generation and editing tasks, with model weights and local-use guidance provided by the project. Check the model-specific resolution and VRAM requirements before choosing a setup.
The facts
Each one read from Wan's own pages, with the date it was checked.
What it does
- Commercial use
- Yeschecked 19 Sep 2026
- Downloads
- Model weights are linked for download through Hugging Face and ModelScope.checked 8 Oct 2026
- Generation tasks
- The models support text-to-video, image-to-video, video editing, text-to-image, and video-to-audio tasks.checked 8 Oct 2026
- GPU requirement
- The T2V-1.3B model requires 8.19 GB VRAM according to the repository, which also reports about four minutes to generate a five-second 480P video on an RTX 4090 without quantization.checked 8 Oct 2026
- Hardware requirement
- The T2V-1.3B model requires 8.19 GB of VRAM, and the project says it can generate a five-second 480P video on an RTX 4090 in about four minutes without quantization.checked 8 Oct 2026
- Image and video tasks
- The repository lists image-to-video, video editing, text-to-image, and video-to-audio among its supported tasks.checked 8 Oct 2026
- Image-to-video
- Yeschecked 19 Sep 2026
- Installation
- The installation guide documents pip and Poetry installation methods.checked 8 Oct 2026
- Integrations
- The project says Wan2.1 T2V and I2V were integrated into Diffusers and that Wan2.1 was integrated into ComfyUI.checked 8 Oct 2026
- License
- The repository identifies its license as Apache-2.0.checked 8 Oct 2026
- Local interface
- The repository includes instructions for running a local Gradio interface.checked 8 Oct 2026
- Maximum resolution
- 720pchecked 19 Sep 2026
- Maximum video length
- 0.083333checked 19 Sep 2026
- Model downloads
- The project provides model downloads through Hugging Face and ModelScope.checked 8 Oct 2026
- Product
- Wan2.1 is an open suite of video foundation models for video generation.checked 8 Oct 2026
- Prompt extension
- Prompt extension can use the DashScope API or a local Qwen model.checked 8 Oct 2026
- Requirements
- The quickstart says to ensure PyTorch 2.4.0 or later before installing dependencies.checked 8 Oct 2026
- Resolutions
- The repository lists T2V-14B at 480P and 720P, and T2V-1.3B at 480P; it cautions that 1.3B results at 720P are less stable than at 480P.checked 8 Oct 2026
- Resolution support
- The T2V-14B model supports 480P and 720P, while T2V-1.3B supports 480P.checked 8 Oct 2026
- Runtime
- The quickstart instructs users to install dependencies with PyTorch 2.4.0 or later and provides command-line and local Gradio inference examples.checked 8 Oct 2026
- Support
- The repository directs users to Discord and WeChat groups to contact the research or product teams.checked 8 Oct 2026
- Text generation
- Wan2.1 can generate Chinese and English text within videos.checked 8 Oct 2026
- Text to video
- Wan2.1 supports text-to-video generation with 1.3B and 14B models.checked 8 Oct 2026
- Text-to-video
- Yeschecked 19 Sep 2026
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