Nemotron-3-Super-120B-A12B Overview

Description:

This container houses Nemotron-3-Super-120B-A12B, which is a large language model (LLM) trained by NVIDIA, designed to deliver strong agentic, reasoning, and conversational capabilities. It is optimized for collaborative agents and high-volume workloads such as IT ticket automation. Like other models in the family, it responds to user queries and tasks by first generating a reasoning trace and then concluding with a final response. The model's reasoning capabilities can be configured through a flag in the chat template.

The model employs a hybrid Latent Mixture-of-Experts (LatentMoE) architecture, utilizing interleaved Mamba-2 and MoE layers, along with select Attention layers. Distinct from the Nano model, the Super model incorporates Multi-Token Prediction (MTP) layers for faster text generation and improved quality, and it is trained using NVFP4 quantization to maximize compute efficiency. The model has 12B active parameters and 120B parameters in total.

The supported languages include: English, French, German, Italian, Japanese, Spanish, and Chinese

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

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.

The use of any models in this container is governed by the NVIDIA Open Model Agreement in addition to any terms which govern the specific models used.

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

The use of this model is governed by the NVIDIA Nemotron Open Model License.

Deployment Geography:

Global

Release Date:

Huggingface 3/11/2026 via\nhttps://huggingface.co/

NGC 3/11/2026 via
\nhttps://catalog.ngc.nvidia.com/orgs/nvstaging/teams/nim/containers/nemotron-3-super-ga

Program Classes

NVIDIA-Nemotron-3-Super-120B-A12B Container includes the following model:

\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
NVIDIA-Nemotron-3-Super-120B-A12B	Nemotron-3-Super-120B-A12B is a general purpose reasoning and chat model that employs a hybrid Latent Mixture-of-Experts (LatentMoE) architecture, utilizing interleaved Mamba-2 and MoE layers, along with select Attention layers. The model has 12B active parameters and 120B parameters in total.	Manual

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.

Documentation

Visit the NIM Container LLM page for release documentation, deployment guides, and more.

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 teams to ensure these software components meet requirements for the relevant industry and use case and addresses unforeseen product misuse.

Please report quality , risk , security vulnerabilities or NVIDIA AI Concerns here.

Get Help

NVIDIA Developer Community Forum

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

Enterprise Support

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

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It is optimized for collaborative agents and high-volume workloads such as IT ticket automation. Like other models in the family, it responds to user queries and tasks by first generating a reasoning trace and then concluding with a final response. The model's reasoning capabilities can be configured through a flag in the chat template.\n\nThe model employs a hybrid **Latent Mixture-of-Experts (LatentMoE)** architecture, utilizing interleaved Mamba-2 and MoE layers, along with select Attention layers. Distinct from the Nano model, the Super model incorporates **Multi-Token Prediction (MTP)** layers for faster text generation and improved quality, and it is trained using **NVFP4** quantization to maximize compute efficiency. The model has **12B active parameters** and **120B parameters in total**.\n\nThe supported languages include: English, French, German, Italian, Japanese, Spanish, and Chinese\n\nThe container components are ready for commercial/non-commercial use.\n\n### **License/Terms of Use:**\n\n**GOVERNING TERMS:** The NIM container is governed by the [NVIDIA Software License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/) and the [Product-Specific Terms for NVIDIA AI Products](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/).\n\nThe use of any models in this container is governed by the [NVIDIA Open Model Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-agreement/) in addition to any terms which govern the specific models used.\n\nYou are responsible for ensuring that your use of any provided models complies with all applicable laws.\n\nThe use of this model is governed by the [NVIDIA Nemotron Open Model License](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-nemotron-open-model-license/).\n\n\n### **Deployment Geography:**\n\nGlobal \n\n### **Release Date:**\n\nHuggingface 3/11/2026 via\n[https://huggingface.co/](https://huggingface.co/) \n\nNGC 3/11/2026 via \nhttps://catalog.ngc.nvidia.com/orgs/nvstaging/teams/nim/containers/nemotron-3-super-ga \n\n## Program Classes\n\nNVIDIA-Nemotron-3-Super-120B-A12B Container includes the following model:\n\n| Model Name & Link | Use Case | How to Pull the Model |\n| :---- | :---- | :---- |\n| [NVIDIA-Nemotron-3-Super-120B-A12B](https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/models/nemotron-3-super-120b-a12b) | Nemotron-3-Super-120B-A12B is a general purpose reasoning and chat model that employs a hybrid Latent Mixture-of-Experts (LatentMoE) architecture, utilizing interleaved Mamba-2 and MoE layers, along with select Attention layers. The model has 12B active parameters and 120B parameters in total. | Manual |\n\n## Deployment Details:\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**Documentation**\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\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\n## **Ethical Considerations:**\n\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 teams to ensure these software components meet requirements for the relevant industry and use case and addresses 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\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\n### Enterprise Support\nGet access to knowledge base articles and support cases or [submit a ticket](https://www.nvidia.com/en-us/data-center/products/ai-enterprise-suite/support/).",["D",1789667634608],[302,300,298,296,294,292,290,288,286,284,282,190,279,273,271,275,269,267,265,304,277,262],"/api/image/nim/nvidia/containers/nemotron-3-super-120b-a12b",12825582968,{"_337":338,"_339":340,"_341":342,"_343":26,"_344":345},"hasSignedTag",[328,329],[326],[],[322],[],{"_93":323,"_125":323,"_126":324,"_128":325},"signed images",{"_130":325,"_125":323},"system",{"_93":124,"_125":124,"_126":327,"_128":129},{"_130":129,"_125":124},{"_93":335,"_125":335,"_126":336,"_128":333},{"_93":330,"_125":331,"_126":332,"_128":333},"NVIDIA NIM","nimmcro_nvidia_nim",{"_130":334,"_125":331},"feature","nvidia_nim","NVIDIA AI Enterprise Supported",{"_130":129,"_125":335},"governingTerms","

The NIM container is governed by the NVIDIA Software License Agreement (https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/) and AI Product-Specific Terms for NVIDIA AI Products (https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/).

The use of any models in this container is governed by the NVIDIA Open Model License Agreement (found at https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/) in addition to any terms which govern the specific models used.

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

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This tracking cookie allows a website to link visitor behaviour to the recipient of an email marketing campaign, to measure campaign effectiveness.","investor.nvidia.com","This cookie is associated with Eventbrite and is used to deliver content tailored to the end user's interests and improve content creation. This cookie is also used for event-booking purposes.","_gat_gtag_UA_140825383_2","Google Analytics","_rdt_uuid","This cookie is set by Reddit and is used for tracking the views of embedded videos and performance of the advertisements.","catalog.ngc.nvidia.com","_uetsid","This cookie is used by Bing to determine what ads should be shown that may be relevant to the end user perusing the site. 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If you do not allow these cookies, then some or all of these services may not function properly.",[663,664,665,666,667,668,669,670,671,672,673,674,675,676,677,678,679,680,681,682,683,684,685,686,687],[634,635,636,637,638],{"_473":548,"_93":548,"_92":106,"_447":658},{"_473":522,"_93":522,"_92":106,"_447":653},{"_473":648,"_93":648,"_92":106,"_447":649},{"_473":643,"_93":643,"_92":106,"_447":644},{"_473":639,"_93":639,"_92":106,"_447":640},"nvidia.partners",[641],{"_263":642,"_479":639,"_480":26,"_92":516},"edge","app.hushly.com",[645],{"_263":646,"_479":643,"_480":26,"_92":647},"*CORS","This domain is associated with Hushly, a platform that provides lead conversion solutions for content marketing by using personalization and content engagement strategies.","github.com",[650],{"_263":651,"_479":648,"_480":26,"_92":652},"_octo","This domain is owned by Github. 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These cookies may store a unique ID so that our system will remember you when you return. Information collected with these cookies is used to measure and find ways to improve website performance.",[746,747,748,749,750,751,752,753,754,755,756,757,758,759,760,761,762,763,764,765,766,767,768,769,770,771,772,773,774],[726,727,728,729],{"_473":741,"_93":741,"_92":106,"_447":742},{"_473":736,"_93":736,"_92":106,"_447":737},{"_473":535,"_93":535,"_92":106,"_447":733},{"_473":648,"_93":648,"_92":106,"_447":730},[731],{"_263":732,"_479":648,"_480":136,"_92":652},"_gh_sess",[734],{"_263":735,"_479":535,"_480":136,"_92":542},"YSC","bizible.com",[738],{"_263":739,"_479":736,"_480":26,"_92":740},"_BUID","Bizible is a marketing attribution software that tracks the performance of marketing efforts and connects them to revenue, primarily used for B2B environments.","a.usbrowserspeed.com",[743],{"_263":744,"_479":741,"_480":26,"_92":745},"tuid","This domain is owned by Ookla which provides internet speed testing services through its Speedtest application.",{"_263":816,"_479":594,"_480":26,"_92":817},{"_263":801,"_479":815,"_480":136,"_92":802},{"_263":784,"_479":597,"_480":26,"_92":709},{"_263":784,"_479":697,"_480":26,"_92":709},{"_263":813,"_479":594,"_480":26,"_92":814},{"_263":801,"_479":600,"_480":136,"_92":802},{"_263":811,"_479":594,"_480":26,"_92":812},{"_263":801,"_479":597,"_480":136,"_92":802},{"_263":809,"_479":696,"_480":26,"_92":810},{"_263":801,"_479":718,"_480":136,"_92":802},{"_263":781,"_479":597,"_480":26,"_92":783},{"_263":807,"_479":594,"_480":136,"_92":808},{"_263":805,"_479":594,"_480":26,"_92":806},{"_263":803,"_479":594,"_480":136,"_92":804},{"_263":801,"_479":692,"_480":136,"_92":802},{"_263":799,"_479":594,"_480":26,"_92":800},{"_263":797,"_479":594,"_480":26,"_92":798},{"_263":795,"_479":594,"_480":136,"_92":796},{"_263":793,"_479":701,"_480":26,"_92":794},{"_263":781,"_479":692,"_480":26,"_92":783},{"_263":791,"_479":594,"_480":26,"_92":792},{"_263":789,"_479":594,"_480":136,"_92":790},{"_263":787,"_479":594,"_480":26,"_92":788},{"_263":785,"_479":594,"_480":26,"_92":786},{"_263":784,"_479":594,"_480":26,"_92":709},{"_263":781,"_479":782,"_480":26,"_92":783},{"_263":779,"_479":594,"_480":26,"_92":780},{"_263":777,"_479":594,"_480":136,"_92":778},{"_263":775,"_479":594,"_480":26,"_92":776},"_ga_xxxxxxxxxx","Used by Google Analytics to identify and track an individual session with your device.","s_ppvl","This cookie is set by Adobe Analytics to store information on the percentage of the page displayed to the end user.","coveo_visitorId","This cookie name is associated with Coveo which is used to store a unique user ID for marketing purposes and to track the number of distinct users who submitted a query or clicked an item, counting them only once even if they did the same query or clicked the same item over the course of many visits.","_dd_s","marketplace.nvidia.com","Datadog Cookie used to group all events generated from a unique user session across multiple pages. 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