Discover the future of AI-generated videos with Wan 2.2. Browse our curated collection of high-quality videos and resources. Experience what's possible with cutting-edge video generation technology.
Discover amazing AI-generated videos created with Wan 2.2 technology. From artistic expressions to technical demonstrations.
Complex character movements with realistic motion dynamics and environmental interaction
Artistic visual storytelling with advanced lighting and composition techniques
Professional-grade video effects with smooth camera movements and transitions
Realistic outdoor scenes with natural lighting and atmospheric effects
Ultra-clear video quality with fine detail preservation and texture accuracy
Cutting-edge wan2.2 AI video technology showcasing complex visual processing capabilities
Experience the next generation of AI video technology with enhanced capabilities and unprecedented quality.
Generate stunning 1080p videos with cinematic-level aesthetics and smooth motion dynamics using our enhanced MoE architecture.
Transform text descriptions and static images into dynamic video content with precise motion control and realistic physics simulation.
Built on open-source technology, Wan 2.2 AI is accessible to creators worldwide with support for consumer-grade GPUs.
Create videos with sophisticated camera movements, realistic physics, and complex scene transitions that were previously impossible.
Scalable solutions designed for businesses, content creators, and professionals with commercial licensing and enterprise support.
Support for various output formats including 480p, 720p, and 1080p to meet different platform requirements and bandwidth needs.
Powered by cutting-edge innovations including MoE architecture, enhanced training data, and high-compression video generation capabilities.
Wan2.2 introduces a Mixture-of-Experts (MoE) architecture into video diffusion models. By separating the denoising process across timesteps with specialized powerful expert models, wan2.2 enlarges the overall model capacity while maintaining the same computational cost.
Wan2.2 incorporates meticulously curated aesthetic data, complete with detailed labels for lighting, composition, contrast, color tone, and more. This allows wan2.2 for more precise and controllable cinematic style generation.
Compared to Wan2.1, Wan2.2 is trained on significantly larger data, with +65.6% more images and +83.2% more videos. This expansion notably enhances wan2.2 model's generalization across multiple dimensions.
Wan2.2 open-sources a 5B model built with advanced Wan2.2-VAE that achieves a compression ratio of 16×16×4. This wan2.2 model supports both text-to-video and image-to-video generation at 720P resolution with 24fps.
| Model | Type | Resolution | Parameters | Description |
|---|---|---|---|---|
| T2V-A14B | Text-to-Video | 480P & 720P | 14B (MoE) | Advanced text-to-video generation with wan2.2 MoE architecture |
| I2V-A14B | Image-to-Video | 480P & 720P | 14B (MoE) | High-quality image-to-video conversion using wan2.2 |
| TI2V-5B | Hybrid T2V+I2V | 720P | 5B | Efficient unified wan2.2 model for consumer GPUs |
Get started with Wan 2.2 AI using our comprehensive installation guide and usage examples for different wan2.2 model configurations.
Download the latest Wan2.2 codebase from our official GitHub repository for wan2.2.
Install all required packages including PyTorch >= 2.4.0 and flash_attn for optimal wan2.2 performance.
Download pre-trained wan2.2 models from HuggingFace or ModelScope for immediate use.
Common questions and detailed answers about Wan 2.2 AI technology and wan2.2 models
Wan 2.2 AI is the latest generation of AI video generation technology featuring Mixture-of-Experts (MoE) architecture, cinematic-level aesthetics, and enhanced motion generation capabilities. Compared to Wan 2.1, wan2.2 is trained on +65.6% more images and +83.2% more videos, achieving top performance among both open-source and closed-source models.
We offer three main models: T2V-A14B for text-to-video (requires 80GB+ VRAM), I2V-A14B for image-to-video (requires 80GB+ VRAM), and TI2V-5B which is optimized for consumer GPUs like RTX 4090 (24GB VRAM) and supports both text-to-video and image-to-video generation at 720P@24fps using wan2.2.
MoE architecture separates the denoising process across timesteps with specialized expert models - a high-noise expert for early stages focusing on overall layout, and a low-noise expert for later stages refining video details. This wan2.2 approach provides 27B total parameters with only 14B active per step, maintaining inference computation while increasing wan2.2 model capacity.
For T2V/I2V-A14B models, you need 80GB+ VRAM (A100, H100), PyTorch >= 2.4.0, and multi-GPU setup is recommended. For the TI2V-5B wan2.2 model, you only need 24GB+ VRAM (RTX 4090), single GPU is sufficient, and it supports 720P@24fps generation on consumer-grade hardware.
You can start by visiting our gallery to explore example videos, then click "Explore Videos" or "Get Started" to access the wan2.2 generation platform. For developers, clone our repository from GitHub, install dependencies with pip, and download the appropriate wan2.2 model from HuggingFace or ModelScope based on your hardware requirements.
Wan 2.2 incorporates meticulously curated aesthetic data with detailed labels for lighting, composition, contrast, and color tone. This enables precise cinematic-style generation with customizable aesthetic preferences. The enhanced training data and wan2.2 MoE architecture result in superior motion complexity, semantic understanding, and visual fidelity.
Comprehensive documentation, installation guides, and usage examples are available on our GitHub repository. You can also download wan2.2 models directly from HuggingFace or ModelScope. For additional support, refer to our installation guide section above or check our Privacy Policy and Terms of Service for wan2.2 platform usage guidelines.