NVIDIA-Nemotron-3-Nano

Model Overview

Model Developer: NVIDIA Corporation

Model Dates:

September 2025 - December 2025

Data Freshness:

• The post-training data has a cutoff date of November 28, 2025.
• The pre-training data has a cutoff date of June 25, 2025.

Description

Nemotron-3-Nano-30B-A3B-BF16 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 6 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.

This model is ready for commercial use.

What is Nemotron?

NVIDIA Nemotron™ is a family of open models with open weights, training data, and recipes, delivering leading efficiency and accuracy for building specialized AI agents.

To get started, you can use our quickstart guide below.

License/Terms of Use

Governing Terms: Use of this model is governed by the NVIDIA Nemotron Open Model License.

Reasoning Benchmark Evaluations

We evaluated our model on the following benchmarks:

All evaluation results were collected via Nemo Evaluator SDK and Nemo Skills. The open source container on Nemo Skills packaged via NVIDIA’s Nemo Evaluator SDK used for evaluations can be found here. In addition to Nemo Skills, the evaluations also used dedicated packaged containers for Tau-2 Bench, ArenaHard v2, AA_LCR. A reproducibility tutorial along with all configs can be found in Nemo Evaluator SDK examples. The configs are also available in this HF repo here. * denotes the accuracy numbers are measured by us.

Deployment Geography: Global

Use Case

NVIDIA-Nemotron-3-Nano-30B-A3B-BF16 is a general purpose reasoning and chat model intended to be used in English and coding languages. Other non-English languages (English, Spanish, French, German, Japanese, Italian) are also supported. This model is intended to be used by developers designing AI Agent systems, chatbots, RAG systems, and other AI-powered applications. This model is also suitable for typical instruction-following tasks.

Release Date

December 15, 2025 via Hugging Face

Reference(s)

• NVIDIA Nemotron 3 model family on Hugging Face
• NVIDIA Nemotron 2 model family on Hugging Face
• Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
• NVIDIA Nemotron 3 White Paper

Model Architecture

• Architecture Type: Mamba2-Transformer Hybrid Mixture of Experts (MoE)
• Network Architecture: Nemotron Hybrid MoE
• Number of model parameters: 30B

Model Design

The model was trained with 25T tokens, with a batch si