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LatestQwen · AlibabaWan2.2-TI2V-5B
Qwen · AlibabaText → Video

Qwen Releases Wan2.2, a 5B Open-Source Video Model

The new Apache 2.0 licensed model from Alibaba's team generates video from either text prompts or still images, offering a unified approach in a compact package.

Jul 28, 2025
NotableApache 2.0
Wan2.2-TI2V-5B

Alibaba's Qwen team has released Wan2.2-TI2V-5B, a new open-source model for video generation. At five billion parameters, the model offers a relatively compact solution for creating short video clips and is available under the permissive Apache 2.0 license, allowing for commercial use.

A key feature of Wan2.2-TI2V-5B is its unified architecture for handling multiple input types. It can generate video from a text description (text-to-video) or animate a still image based on a prompt (image-to-video). This flexibility is packaged for broad accessibility, with the official release available in the popular Diffusers format.

A Versatile Tool for Generative Video

The release adds another strong contender to the rapidly evolving open-source video landscape. Its 5B parameter size strikes a balance between capability and accessibility, potentially enabling more developers and researchers to experiment with high-quality video generation without requiring massive computational resources.

The model's dual-input nature and commercial-friendly license position it as a versatile foundation for building creative applications. Developers can access the weights and usage examples for Wan2.2-TI2V-5B on the Hugging Face Hub.

Sources

  • Wan-AI/Wan2.2-TI2V-5B-Diffusers

    Hugging Face

    Visit
OlderQwen Unveils Wan2.2, a 14B Open Text-to-Video ModelQwen · Alibaba · Text → Video · last yearNewerTencent Releases Wan2.2, a 14B MoE Video ModelTencent · Text → Video · last year

Get the model

Hugging Face

Specs

Parameters5B
Resolution1280×704
Frame rate24 fps
Size20 GB
PrecisionFP32
ArchitectureWanPipeline
LicenseAPACHE-2.0
Downloads19.1K
Likes909

Can you run it?

Runs on a laptop — about 6 GB at FP8.

  • FP32 (as published)

    24 GB GPU (RTX 3090 / 4090) · 32 GB Mac

    21 GB
  • 16-bit

    12 GB GPU (RTX 3060 / 4070) · 16 GB Mac

    11 GB
  • FP8

    8 GB GPU (RTX 4060) · 16 GB laptop or Mac

    6 GB
Your machine
  • Covers the published checkpoint; text encoders and VAE loaded alongside may add a few GB (many runtimes offload them to CPU).

Based on Hugging Face weights metadata. Assumes an 8K context and ~1 GB runtime overhead; actual needs vary. How we estimate


Modalities

Image → VideoText → Video
2 versions — view changelog

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