Nemotron 3 Nano - A new Standard for Efficient, Open, and Intelligent Agentic Models

NVIDIA's Nemotron 3 Nano is a newly developed AI model designed to enhance the efficiency and accuracy of multi-agent systems, especially in long-context and high-throughput scenarios. It features a hybrid architecture combining Mamba-Transformer and a sparse Mixture-of-Experts (MoE) design, which allows it to achieve remarkable efficiency and accuracy in reasoning tasks while maintaining a cost-effective profile. With a 1M-token context window and a unique reasoning ON/OFF functionality, Nemotron 3 Nano excels in complex agentic workflows, such as math, coding, and multi-step tool use. NVIDIA also introduces NeMo Gym, an open-source library for building reinforcement learning environments, to aid in the development and scaling of reinforcement learning tasks. This release includes extensive datasets, training recipes, and open weights, aiming to facilitate innovation and deployment in AI-driven multi-agent systems.