Wan2.2

What is Wan2.2?

Wan2.2 is the world's first open-source Mixture-of-Experts (MoE) video generation model, developed by Alibaba Tongyi Lab. It enables users to create professional cinematic videos from text or images at 720P resolution with 24fps output. The model leverages advanced MoE architecture to enlarge model capacity while maintaining computational efficiency, delivering superior quality and realistic motion. Wan2.2 offers both text-to-video (T2V) and image-to-video (I2V) capabilities. The I2V-A14B model brings static images to life with stable video synthesis, reducing unrealistic camera movements at both 480P and 720P resolutions. It excels at recreating complex motions such as hip-hop dancing, street parkour, and figure skating with enhanced fluidity and natural movement patterns. Key features include precise prompt following, fine-grained control over lighting, color, and composition, and professional cinematic output quality. The model is fully open-source with complete model weights available on GitHub. It is trained on over 65.6% more images than previous versions, enhancing generalization across diverse motion scenarios. Wan2.2 is ideal for filmmakers, content creators, and developers seeking high-quality video generation with cinematic control. Use cases include creating dynamic sequences from images, generating video content for marketing, storytelling, and animation. The optimized visual generation pipeline allows users to create images specifically designed for seamless video integration, with aesthetic data fine-tuning for lighting, composition, and color. Technical details include support for 480P and 720P resolutions, MoE architecture for efficient scaling, and reduced unrealistic camera movements. Wan2.2 represents a significant advancement in open-source video generation, making professional-grade tools accessible to everyone.

Use Cases

Key Features

text to video generation image video synthesis 720P 24fps output Mixture of Experts architecture professional cinematic quality precise prompt following fine grained visual control realistic motion recreation open source model weights enhanced motion fluidity

Who is it for?

filmmakers, content creators, video editors, AI researchers, developers, media production teams, creative agencies

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