1. Tutorial Introduction

NVIDIA-Nemotron-Nano-9B-v2 is a lightweight large language model released by the NVIDIA team on August 19, 2025. As a hybrid architecture optimized version of the Nemotron series, this model innovatively integrates the efficient long sequence processing of Mamba with the strong semantic modeling capabilities of Transformer. It achieves 128K ultra-long context support with only 9 billion (9B) parameters. Its inference efficiency and task performance on edge computing devices (such as RTX 4090-level GPUs) are comparable to state-of-the-art models with similar parameter sizes, marking a significant breakthrough in lightweight deployment and long text understanding for large language models. Related research papers are available. NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model .

This tutorial uses a single RTX A6000 card as the resource.

2. Project Examples

3. Operation steps

1. After starting the container, click the API address to enter the Web interface

2. After entering the webpage, you can start a conversation with the model

If "Model" is not displayed, it means the model is being initialized. Since the model is large, please wait about 2-3 minutes and refresh the page.

How to use

4. Discussion

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Citation Information

The citation information for this project is as follows:

@misc{nvidia2025nvidianemotronnano2,
      title={NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model},
      author={NVIDIA},
      year={2025},
      eprint={2508.14444},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2508.14444},
}