Wan 2.2
Wan 2.2 is an advanced open-source AI video generation model featuring a Mixture-of-Experts architecture, enhanced data scaling, and cinematic aesthetics control, enabling high-quality text-to-video and image-to-video generation at 720P resolution with 24fps on consumer-grade GPUs.
Wan 2.2 is ai video generation software teams evaluate for creative & design. Use this page to review pricing, integration signals, and the best alternatives before you commit.
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Quick Overview
Best for: Creative & Design
What it does
AI Video Generation software for decision-makers comparing workflow fit and alternatives.
Best fit
Creative & Design
Pricing snapshot
Free
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Wan 2.2
Wan 2.2 is a major upgrade to the Wan AI video generation models, now open-sourced to provide more powerful capabilities, better performance, and superior visual quality. It introduces a Mixture-of-Experts (MoE) architecture that separates the denoising process into specialized expert models, increasing model capacity without additional computational cost. The model is trained on significantly larger datasets, improving generalization across motions, semantics, and aesthetics. Wan 2.2 supports both text-to-video and image-to-video generation at 720P resolution and 24fps, optimized to run efficiently on consumer-grade GPUs such as the NVIDIA 4090. It is designed for both industrial applications and academic research, offering fine-grained control over cinematic elements like lighting, color, and composition.
Wan 2.2 is the first open-source Mixture-of-Experts (MoE) model for AI video generation, offering top-tier performance and fine-grained cinematic control over lighting, color, and composition.
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Claim this listingKey Features
Mixture-of-Experts (MoE) Architecture
Separates the denoising process into high-noise and low-noise expert models, increasing total model parameters while keeping inference cost nearly unchanged, resulting in superior video generation quality.
Data Scaling
Trained on 65.6% more images and 83.2% more videos compared to Wan 2.1, enhancing generalization across multiple dimensions such as motion, semantics, and aesthetics.
Cinematic Aesthetics Control
Incorporates curated aesthetic data with fine-grained labels for lighting, composition, and color, enabling precise and controllable cinematic style video generation.
Efficient High-Definition Hybrid TI2V
A 5B model with advanced Wan2.2-VAE compression supports text-to-video and image-to-video generation at 720P/24fps, capable of running on consumer-grade GPUs with fast generation speeds.
Open Source Availability
Wan 2.2 is fully open-sourced, allowing access to powerful video generation models for both industrial and academic use.
Pricing
Wan 2.2 is fully open-sourced and available for free, enabling unrestricted access to its video generation models.
Use Cases
Professional Cinematic Video Production
Create videos with fine-grained control over lighting, color, and composition to achieve professional cinematic narratives.
Text-to-Video Generation
Generate high-quality videos from textual descriptions at 720P resolution and 24fps for creative and commercial applications.
Image-to-Video Generation
Transform images into dynamic videos with stable synthesis and reduced unrealistic camera movements.
Motion and Action Recreation
Effortlessly recreate complex motions such as hip-hop dancing, fight scenes, parkour, figure skating, and more with enhanced fluidity and control.
Academic Research
Use the open-source models and benchmark results for advancing research in video generation and diffusion models.
Integrations
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Benefits
Limitations
Frequently Asked Questions
What is the Mixture-of-Experts (MoE) architecture in Wan 2.2?
Can Wan 2.2 run on consumer-grade GPUs?
What resolutions and frame rates does Wan 2.2 support?
Is Wan 2.2 suitable for both text-to-video and image-to-video generation?
Where can I access the Wan 2.2 models?
Getting Started
- 1 Visit the official website at https://wan.video/welcome to access resources and model downloads.
- 2 Choose the appropriate Wan 2.2 model variant (e.g., T2V-A14B, I2V-A14B, TI2V-5B) based on your use case.
- 3 Follow the provided instructions and documentation to set up the model on your hardware, ensuring compatibility with consumer-grade GPUs like the NVIDIA 4090.
Support
Documentation
Comprehensive documentation and model details are available on the official website and Hugging Face pages.
Community
Users can engage with the community and developers through forums and GitHub repositories linked from the official site.
API
No specific API documentation mentioned; models are available for download and local deployment.
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