ERNIE-Image Container Overview
Description:
This container houses the ERNIE-Image model, which is an open text-to-image generation model built on an 8B single-stream Diffusion Transformer and paired with a lightweight Prompt Enhancer, achieving strong performance in complex instruction following, text rendering (including dense, long-form text in English and Chinese), and structured image generation (e.g., posters, comics, multi-panel layouts).
The container components are ready for commercial/non-commercial use.
Third-Party Community Consideration:
The model embedded in the container is not owned or developed by NVIDIA. This model has 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:
- HuggingFace: ERNIE-Image version April 14, 2026 via https://huggingface.co/baidu/ERNIE-Image
- build.nvidia.com October 15, 2026 via https://build.nvidia.com/baidu/ernie-image
ERNIE-Image:
The ERNIE-Image Container includes the following model:
| Model Name & Link | Use Case | How to Pull the Model |
|---|---|---|
| ERNIE-Image https://huggingface.co/baidu/ERNIE-Image | Performs text-to-image generation with complex instruction following, text rendering, and structured layout generation. | Automatic |
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/baidu/ernie-image:latest
Key Considerations:
The model 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.
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