NVIDIA
NVIDIA
qwen-image
Container
NVIDIA
NVIDIA
qwen-image

Qwen Image model is an image generation foundation model (Visual GenAI model) in the Qwen series, achieving significant advances in complex text rendering and precise image editing.

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Qwen-Image Container Overview

Description:

This container houses the Qwen Image model, which is an image generation foundation model in the Qwen series, achieving significant advances in complex text rendering (supporting alphabetic languages like English and logographic languages like Chinese) and precise image editing (e.g., style transfer, object addition/removal, pose manipulation).

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:

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:

Qwen Image:

The Qwen Image Container includes the following models:

Model Name & LinkUse CaseHow to Pull the Model
Qwen-Image https://huggingface.co/Qwen/Qwen-ImagePerforms image generation for complex text rendering.Automatic
Qwen-Image-2512 https://huggingface.co/Qwen/Qwen-Image-2512Updated version of Qwen-Image model with enhanced human realism, finer natural detail, and improved text renderingAutomatic

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

Container Version(s):

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

Key Considerations:

The models embedded in this container can generate synthetic images 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 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. 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.

Enterprise Support

Get access to knowledge base articles and support cases or submit a ticket.

Publisher
NVIDIA
NVIDIA
LicenseNVIDIA proprietary
Latest Taglatest
UpdatedJuly 14, 2026 UTC
Compressed Size14.35 GB
Multinode SupportNo
Multi-Arch SupportYes

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