Qwen-Image-Edit Container Overview

Description:

This container houses the Qwen Image Edit model family, which successfully extends Qwen-Image’s unique text rendering capabilities to image editing tasks, enabling precise text editing.

The container components are ready for commercial/non-commercial use.

Third-Party Community Consideration:

The models embedded in the container are not owned or developed by NVIDIA. These models have been developed and built to a third-party’s requirements for this application and use case; see link to:

• Qwen/Qwen-Image-Edit Model Card
• Qwen/Qwen-Image-Edit-2509 Model Card
• Qwen/Qwen-Image-Edit-2511 Model Card

License/Terms of Use:

GOVERNING TERMS: The NIM container is governed by the NVIDIA Software License Agreement and the Product-Specific Terms for NVIDIA AI Products. Use of this model is governed by the NVIDIA Open Model License. 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:

• HuggingFace/Modelscope: Qwen-Image-Edit version August 18, via https://huggingface.co/Qwen/Qwen-Image-Edit and https://modelscope.cn/models/Qwen/Qwen-Image-Edit
• HuggingFace/Modelscope: Qwen-Image-Edit-2509 version September 22, via https://huggingface.co/Qwen/Qwen-Image-Edit-2509 and https://modelscope.cn/models/Qwen/Qwen-Image-Edit-2509
• HuggingFace/Modelscope: Qwen-Image-Edit-2511 version December 23, via https://huggingface.co/Qwen/Qwen-Image-Edit-2511 and https://modelscope.cn/models/Qwen/Qwen-Image-Edit-2511
• build.nvidia.com March 11, 2026 via https://build.nvidia.com/qwen/qwen-image-edit

Qwen Image:

The Qwen Image Edit Container includes the following models:

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.

References

• Technical Report Publication

Container Version(s):

nvcr.io/nim/qwen/qwen-image-edit:latest

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. When downloaded or used in accordance with our terms of service, 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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