NVIDIA
Wan2.2-Animate-2-14B
Container
NVIDIA
Wan2.2-Animate-2-14B

Wan-Animate-2 is a novel end-to-end character animation framework

Wan2.2-Animate-2-14B Container Overview

Description:

This NIM container houses the Wan-Animate-2, a novel end-to-end character animation framework that directly consumes driving videos in a redesigned Diffusion Transformer, which achieves high-fidelity motion generation and strong identity preservation by eliminating intermediate motion extractors. We further add text-driven viewpoint control to decouple the output camera perspective from the driving video. The container components are ready for commercial or non-commercial use.

Third-Party Community Consideration:

This model is not owned or developed by NVIDIA. This model have been developed and built to a third-party’s requirements for this application and use case; see links to:

License/Terms of Use:

GOVERNING TERMS: The use of the NIM container is governed by the NVIDIA Software and Model Evaluation License. The use of the model is governed by the NVIDIA Open Model Agreement. Additional Information: Apache 2.0 license.

You are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws.

Deployment Geography:

Global

Release Date:

Wan 2.2:

The Wan2.2-Animate-2-14B Container includes the following models:

Model Name & LinkUse CaseHow to Pull the Model
Wan-AI/Wan2.2-Animate-2-14B https://huggingface.co/Wan-AI/Wan2.2-Animate-2-14B-Diffusersvideo generation with high-fidelity motion generation and strong identity preservationAutomatic

Deployment Details:

Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA’s hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster training and inference times compared to CPU-only solutions.

Container Version(s):

nvcr.io/nim/wan-ai/wan2.2-animate-2-14b:latest

Key Considerations:

The model embedded in this container can generate synthetic videos and may produce content that is inaccurate, offensive, or otherwise inappropriate. Users should implement robust safety guardrails — including content filtering, abuse monitoring, and access controls— to reduce the risk of harmful outputs. Users are responsible for ensuring that their use of the model complies with all applicable laws and regulations, and for regularly reviewing and updating their guardrails as risks evolve.

For more information about the implementation of Cosmos pre- and post-processing guardrails to improve model safety, please see the Cosmos-1.0 Guardrail Model.

Security Common Vulnerabilities and Exposures (CVEs)

Please review the Security Scanning tab on NGC to view the latest security scan results. For certain open-source vulnerabilities listed in the scan results, NVIDIA provides a response in the form of a Vulnerability Exploitability eXchange (VEX) document. The VEX information can be reviewed and downloaded from the Security Scanning tab.

Ethical Considerations:

NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. Developers should work with their internal developer team to ensure these software components meet requirements for the relevant industry and use case and address unforeseen product misuse.

Please make sure you have proper rights and permissions for all input image and video content; if image or video includes people, personal health information, or intellectual property, the image or video generated will not blur or maintain proportions of image subjects included.

Users are responsible for model inputs and outputs. Users are responsible for ensuring safe integration of this model, including implementing guardrails as well as other safety mechanisms, prior to deployment.

Please report model quality, risk, security vulnerabilities or NVIDIA AI Concerns here.

Get Help

Getting started with the NIM

Deploying and integrating the NIM is straightforward thanks to our industry standard APIs. Visit the Visual Generative AI NIM page for release documentation, deployment guides and more.

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Publisher
NVIDIA
LicenseNVIDIA proprietary
Latest Taglatest
UpdatedAugust 19, 2026 UTC
Compressed Size19.63 GB
Multinode SupportNo
Multi-Arch SupportYes

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