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 https://huggingface.co/

NGC 3/11/2026 via
https://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:

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. 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 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.

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