Wan 2.2

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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Key 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

Free Tier Available

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

Superior video generation quality with advanced MoE architecture.
Enhanced generalization due to significantly larger training datasets.
Precise cinematic style control for customizable video aesthetics.
Efficient generation on consumer-grade GPUs enabling accessibility.
Open-source availability fostering innovation and collaboration.

Limitations

Currently supports up to 720P resolution, which may not meet needs for ultra-high-definition video generation.
Generation speed for 5-second 720P videos is under 9 minutes on a single consumer GPU, which may be slow for some real-time applications.

Frequently Asked Questions

What is the Mixture-of-Experts (MoE) architecture in Wan 2.2?
It is a design that uses two specialized expert models for different denoising stages, increasing model capacity while keeping inference cost stable, resulting in higher quality video generation.
Can Wan 2.2 run on consumer-grade GPUs?
Yes, models like TI2V-5B are optimized to run efficiently on consumer-grade GPUs such as the NVIDIA 4090.
What resolutions and frame rates does Wan 2.2 support?
Wan 2.2 supports video generation at 480P and 720P resolutions with 24 frames per second.
Is Wan 2.2 suitable for both text-to-video and image-to-video generation?
Yes, Wan 2.2 supports both text-to-video and image-to-video generation within a unified framework.
Where can I access the Wan 2.2 models?
The models are open-sourced and available on platforms such as Hugging Face, linked from the official website.

Getting Started

  1. 1 Visit the official website at https://wan.video/welcome to access resources and model downloads.
  2. 2 Choose the appropriate Wan 2.2 model variant (e.g., T2V-A14B, I2V-A14B, TI2V-5B) based on your use case.
  3. 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

Available: No
Documentation:

No specific API documentation mentioned; models are available for download and local deployment.

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