This NIM container houses the Nemotron 3 Content Safety model which, is a small language model (SLM) that uses Google's Gemma-3-4B-it as the base and is fine-tuned by NVIDIA on multimodal and multilingual content-safety related datasets.
Nemotron-3 Content Safety VLM Overview
Description:
This NIM container houses the Nemotron 3 Content Safety model which, is a small language model (SLM) that uses Google's Gemma-3-4B-it as the base and is fine-tuned by NVIDIA on multimodal and multilingual content-safety related datasets. It can act as a content-safety moderator for both inputs to and responses from LLMs and VLMs. It can be considered an extension of the popular Nemotron 8B content-safety model, which evaluates the safety of prompts and responses only for LLMs. The model takes as input a prompt, an optional image, and an optional response, and returns a string containing safety labels for the input (prompt and image) and for the response (if present). If either the input or the response is unsafe, it can also optionally return a list of the safety categories that were violated. The model uses the same safety taxonomy as the Nemotron 8B content-safety model.
The container components are ready for commercial use.
License/Terms of Use:
GOVERNING TERMS: Use of the NIM is governed by the NVIDIA Software and Model Evaluation License Agreement. Use of the model is governed by the NVIDIA Nemotron Open Model License,Gemma Terms of Use and Gemma Prohibited Use Policy.
You are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws.
Deployment Geography:
Global
Release Date:
Build.NVIDIA.com: 04/30/2026 via link)
Hugging Face: 04/16/2026 via link
Program Classes:
The Nemotron-3 Content Safety VLM Container includes the Nemotron-3 Content Safety VLM model.
| Model Name & Link | Use Case | How to Pull the Model |
|---|---|---|
| Nemotron-3 Content Safety VLM | act as a content-safety moderator for both inputs to and responses from LLMs and VLMs. | Automatic |
Deployment Details:
Visit the NIM Container VLM page for release documentation, deployment guides, and more.
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.
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.
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 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 VLM NIM page for release documentation, deployment guides and more.
NVIDIA Developer Community Forum
Get access to community knowledge base articles and support cases here.
Get Help
Getting started with the NIM
Deploying and integrating the NIM is straightforward thanks to our industry standard APIs. Visit the NVIDIA NIM documentation for release documentation, deployment guides and more.
NVIDIA Developer Community Forum
For support, visit the NVIDIA Developer Community Forum.