NVIDIA
NVIDIA
nemotron-nano-3
Container
NVIDIA
NVIDIA
nemotron-nano-3

Nemotron-3-Nano-30B-A3B is a large language model (LLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and non-reasoning tasks.

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Nemotron-3-Nano-30B-A3B

Description:

This container houses Nemotron-3-Nano-30B-A3B, which is a large language model (LLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and non-reasoning tasks. 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. If the user prefers the model to provide its final answer without intermediate reasoning traces, it can be configured to do so, albeit with a slight decrease in accuracy for harder prompts that require reasoning. Conversely, allowing the model to generate reasoning traces first generally results in higher-quality final solutions to queries and tasks.

The model employs a hybrid Mixture-of-Experts (MoE) architecture, consisting of 23 Mamba-2 and MoE layers, along with 6 Attention layers. Each MoE layer includes 128 experts plus 1 shared expert, with 5 experts activated per token. The model has 3.5B active parameters and 30B parameters in total.

The supported languages include: English, German, Spanish, French, Italian, and Japanese. Improved using Qwen.

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.

Use of this model is governed by the NVIDIA Open Model Agreement.

Deployment Geography:

Global

Release Date:

Huggingface 12/10/2025 via
https://huggingface.co/

NGC 12/10/2025 via
https://catalog.ngc.nvidia.com/models

Nemotron-3-Nano-30B-A3B

NVIDIA-Nemotron-3-Nano-30B-A3B Container includes the following model:

Model Name & LinkUse CaseHow to Pull the Model
NVIDIA-Nemotron-3-Nano-30B-A3BNemotron-3-Nano-30B-A3B is a general purpose reasoning and chat model that employs a hybrid Mixture-of-Experts (MoE) architecture, consisting of 23 Mamba-2 and MoE layers, along with 6 Attention layers. Each MoE layer includes 128 experts plus 1 shared expert, with 5 experts activated per token. The model has 3.5B active parameters and 30B 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.
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 model team to ensure this model meets 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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Publisher
NVIDIA
NVIDIA
LicenseNVIDIA proprietary
Latest Tag2.0.6
UpdatedJune 3, 2026 UTC
Compressed Size10.62 GB
Multinode SupportNo
Multi-Arch SupportYes