NVIDIA Nemotron 3: Efficient and Open Intelligence

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Abstract

We introduce the Nemotron 3 family of models - Nano, Super, and Ultra. These models deliver strong agentic, reasoning, and conversational capabilities. The Nemotron 3 family uses a Mixture-of-Experts hybrid Mamba-Transformer architecture to provide best-in-class throughput and context lengths of up to 1M tokens. Super and Ultra models are trained with NVFP4 and incorporate LatentMoE, a novel approach that improves model quality. The two larger models also include MTP layers for faster text generation. All Nemotron 3 models are post-trained using multi-environment reinforcement learning enabling reasoning, multi-step tool use, and support granular reasoning budget control. Nano, the smallest model, outperforms comparable models in accuracy while remaining extremely cost-efficient for inference. Super is optimized for collaborative agents and high-volume workloads such as IT ticket automation. Ultra, the largest model, provides state-of-the-art accuracy and reasoning performance. Nano is released together with its technical report and this white paper, while Super and Ultra will follow in the coming months. We will openly release the model weights, pre- and post-training software, recipes, and all data for which we hold redistribution rights.

Abstract (translated)

我们介绍了 Nemotron 3 模型系列 - Nano、Super 和 Ultra。这些模型提供了强大的代理、推理和对话能力。Nemotron 3 系列采用混合专家组合的 Mamba-Transformer 架构，提供业界领先的吞吐量，并支持长达100万个令牌（token）的上下文长度。Super 和 Ultra 模型使用 NVFP4 进行训练，并集成了 LatentMoE，这是一种新颖的方法，可提高模型的质量。这两个较大的模型还包含了 MTP 层以加速文本生成过程。所有的 Nemotron 3 模型都经过多环境强化学习的后期训练，使得它们在推理、多步骤工具使用以及细粒度推理预算控制方面具备更强的能力。Nano 是最小的模型，在准确性上超越了同类模型，并且在推理时非常经济高效。Super 模型针对协作代理和如 IT 工单自动化等高负载工作场景进行了优化。Ultra 是最大的模型，提供了业界领先的准确性和推理性能。Nano 模型将与技术报告和白皮书一同发布，而 Super 和 Ultra 将在未来几个月内陆续推出。我们将公开发布所有这些模型的权重、预训练和后期训练软件、配方以及我们拥有再分发权利的所有数据。

URL

https://arxiv.org/abs/2512.20856

PDF Copy

https://arxiv.org/pdf/2512.20856.pdf