Nemotron-Content-Safety-Reasoning-4B Overview

Description:

This container houses Nemotron-Content-Safety-Reasoning-4B, which is a Large Language Model (LLM) classifier designed to function as a dynamic and adaptable guardrail for content safety and dialogue moderation (topic-following).

Its primary advantage is the ability to enforce custom safety policies. Users can \"bring their own safety policy,\" and the model will adapt its classification and reasoning to meet those specific, user-defined criteria.

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

License/Terms of Use:

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

Huggingface 11/2025 via
\nhttps://huggingface.co/

NGC 2/23/2026 via
\nhttps://catalog.ngc.nvidia.com/

Program Classes:

The Nemotron-Content-Safety-Reasoning-4B Container includes the following models:

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

tr:nth-child(odd)]:bg-surface-sunken\">

Model Name & Link	Use Case	How to Pull the Model
Nemotron-Content-Safety-Reasoning-4B	Nemotron-Content-Safety-Reasoning-4B, which is a Large Language Model (LLM) classifier designed to function as a dynamic and adaptable guardrail for content safety and dialogue moderation (topic-following).	Manual

Deployment Details:

Visit the NIM Container LLM 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.

Security Common Vulnerabilities and Exposures (CVEs)

Please review the Security Scanning tab on NGC to view the latest security scan results.\nFor 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 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 NIM Container page for release documentation, deployment guides and more the hyperlink.

Get Help

NVIDIA Developer Community Forum

Get access to community knowledge base articles and support cases (https://forums.developer.nvidia.com/)

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

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\n\nThis container houses Nemotron-Content-Safety-Reasoning-4B, which is a Large Language Model (LLM) classifier designed to function as a dynamic and adaptable guardrail for content safety and dialogue moderation (topic-following).\n\nIts primary advantage is the ability to enforce custom safety policies. Users can \"bring their own safety policy,\" and the model will adapt its classification and reasoning to meet those specific, user-defined criteria.\n\nThe container components are ready for commercial/non-commercial use.
\n\n### License/Terms of Use:\nThe NIM container is governed by the [NVIDIA Software License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/) and [Product-Specific Terms for NVIDIA AI Products](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/). Use of this model is governed by the [NVIDIA Open Model License](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/). Additional Information: [Gemma Terms of Use](https://ai.google.dev/gemma/terms) and [Gemma Prohibited Use Policy](https://ai.google.dev/gemma/prohibited_use_policy).\n\nYou are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws.\n\n### Deployment Geography:\nGlobal\n\n### Release Date:
\n\nHuggingface 11/2025 via \n[https://huggingface.co/](https://huggingface.co/nvidia/Nemotron-Content-Safety-Reasoning-4B) \n\nNGC 2/23/2026 via \n[https://catalog.ngc.nvidia.com/](https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/containers/nemotron-content-safety-reasoning-4b)\n\n## Program Classes:
\n\nThe Nemotron-Content-Safety-Reasoning-4B Container includes the following models: \n\n| Model Name & Link | Use Case | How to Pull the Model |\n| :---- | :---- | :---- |\n| Nemotron-Content-Safety-Reasoning-4B | Nemotron-Content-Safety-Reasoning-4B, which is a Large Language Model (LLM) classifier designed to function as a dynamic and adaptable guardrail for content safety and dialogue moderation (topic-following). | Manual |\n\n\n## Deployment Details:
\n\nVisit the [NIM Container LLM](https://docs.nvidia.com/nim/large-language-models/latest/introduction.html) page for release documentation, deployment guides, and more.\n\n\nOur 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.
\n\n## Security Common Vulnerabilities and Exposures (CVEs)\nPlease review the Security Scanning tab on NGC to view the latest security scan results.\nFor 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.\n\n## Ethical Considerations:\nNVIDIA 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.
\n\nPlease report quality, risk, security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/). \n\n\n# Get Help\n\n## Getting started with the NIM\nDeploying and integrating the NIM is straightforward thanks to our industry standard APIs. Visit the NIM Container page for release documentation, deployment guides and more [the hyperlink](https://docs.nvidia.com/nim/large-language-models/latest/introduction.html).\n\n## **Get Help**\n\n### NVIDIA Developer Community Forum\nGet access to community knowledge base articles and support cases (https://forums.developer.nvidia.com/)\n\nYou are responsible for ensuring that your use of NVIDIA provided models complies with all applicable laws.","Nemotron-Content-Safety-Reasoning-4B (Experimental)",["D",1776997256184],[314,255],"/api/image/nim/nvidia/containers/nemotron-content-safety-reasoning-4b-experimental",9710417955,"hasSignedTag",[360],[337,338,339,340,341,342],[],[333],[],{"_95":334,"_165":334,"_166":335,"_168":336},"signed images",{"_170":336,"_165":334},"system",{"_95":356,"_165":357,"_166":358,"_168":169},{"_95":164,"_165":164,"_166":355,"_168":169},{"_95":352,"_165":353,"_166":354,"_168":169},{"_95":348,"_165":349,"_166":350,"_168":169},{"_95":345,"_165":345,"_166":346,"_168":169},{"_95":343,"_165":343,"_166":344,"_168":169},"NSPECT-6M7Q-S30U",{"_170":169,"_165":343},"NeMo",{"_170":347,"_165":345},"framework","Natural Language Understanding","uscs_natural_language_understanding",{"_170":351,"_165":349},"application","Natural Language Processing","uscs_natural_language_processing",{"_170":351,"_165":353},{"_170":169,"_165":164},"AI","soln_ai",{"_170":359,"_165":357},"technology",{"_95":361,"_165":362,"_166":363,"_168":364},"NVIDIA NIM","nimmcro_nvidia_nim",{"_170":365,"_165":362},"feature","nvidia_nim",{"_221":1484,"_223":1485},"ngcApps",[1437],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1418":1419,"_1420":1421,"_1422":1423,"_1424":1425,"_1426":377,"_252":403,"_1427":1428,"_1429":51,"_1430":124,"_1431":124,"_1432":1433,"_1434":124,"_1435":1436},"amplitude",{"_1415":1416,"_1039":-7,"_1417":26},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmVuYWJsZUNzYVdpZGdldCUyMiUzQWZhbHNlJTJDJTIyY29udGFpbmVyU2Nhbm5pbmdSZWRlc2lnbk0yJTIyJTNBdHJ1ZSU3RA==","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1409":1410,"_1411":1412,"_1413":1414},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"manageableExternalUserGroups",[],"ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"now",1794417342110,"1.31.0","defaultSearchSuggestions",{"_1309":485,"_1310":1311,"_1312":1313,"_1314":1315},"announcements",[],"consentState",{"_441":1299,"_1300":26,"_1301":26,"_1302":124,"_1303":1304},"consentConfig",{"_423":424,"_425":426,"_427":428,"_429":430,"_431":432,"_433":434,"_435":436,"_437":438,"_439":440,"_441":442},"showContactAdmin",1794417342111,[],[],[417,418,419,420,421,422],{"_40":62,"_42":67,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":62,"_42":65,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":60,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":55,"_42":56,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":52,"_42":53,"_44":64,"_46":-5,"_48":-5,"_50":51},{"_40":41,"_42":43,"_44":64,"_46":-5,"_48":-5,"_50":51},"mainInfoText","We and our third-party partners (including social media, advertising, and analytics partners) use cookies and other tracking technologies to collect, store, monitor, and process certain information about you when you visit our website. The information collected might relate to you, your preferences, or your device. We use that information to make the site work, analyze performance and traffic on our website, provide a more personalized web experience, and assist in our marketing efforts.

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It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","sessionid","This is a very generic cookie name that may have different purposes on different sites, but generally it will be some kind of anonymous session identifier.","_csrf","This cookie is used to prevent Cross-Site Request Forgery (CSRF) attacks, ensuring that each request made to the server is from the user's browser and is intentional.","enterprise-support.nvidia.com","renderCtx","academicgrants.nvidia.com","Used to store site parameters in the session for reuse across requests by a single client for functionality and performance reasons.","This cookie is managed by AWS and is used for load balancing.Used to attribute commission to affiliates when you arrive at the website from an affiliate referral link. It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","nvidiaCart","This domain is owned by NVIDIA Corporation which provides information about the company, its products, solutions, industries, news, events, and career opportunities.","nv_co","__uxq412__ses.88c1","AWS ELB application load balancerUsed to attribute commission to affiliates when you arrive at the website from an affiliate referral link. It is set when you click on one of our links and used to let the advertiser and us know the website from which you came.","learn.learn.nvidia.com","pctrk","Used to count page views by unauthenticated users against license usage.","bm_s","This cookie is associated with Akamai. It is used to analyse traffic to determine if it is automated traffic generated by bots or a human user.","bpazaws52gukakzc__ctrl0_ctl36_uccaptcha","programs.nvidia.com","bm_sv","store.nvidia.com","The __cf_bm cookie is a cookie necessary to support Cloudflare Bot Management, currently in private beta. 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It is a temporary cookie used to determine if the browser accepts cookies.","XSRF-TOKEN","This cookie is written to help with site security in preventing Cross-Site Request Forgery attacks.This cookie helps with site security in preventing Cross-Site Request Forgery attacks.","bpazaws52gukakzc__ctrl0_ctl78_list_ctl09_systemcaptcha","ph_phc_yQgAEdJJkVpI24NdSRID2mor1x1leRpDoC9yZ9mfXal_posthog","The PostHog ph_phc_xxx cookie is a session cookie used for identifying and tracking visitors on websites, helping us understand user behavior and website performance.","PHPSESSID","PHP session cookie associated with embedded content from this domain.\n","base.manager.learn.nvidia.com","bm_ss","This cookie is used to help protect websites from automated bot traffic.","_devzone_session","This cookie is likely used to maintain a user session on the website by the server. 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