Nemotron 3 Nano 30B A3B is the entry-level tier of NVIDIA's Nemotron 3 family of open models, which also includes the larger Super and Ultra variants. NVIDIA positions the family as its most efficient open lineup for agentic AI, and describes Nano specifically as the smallest member that still outperforms comparable models in accuracy while remaining extremely cost-efficient for inference. The family is aimed at agentic, reasoning, and conversational workloads, with Nano tuned as a unified model that can handle both deliberate chain-of-thought reasoning and direct non-reasoning responses in a single model.

Architecturally, Nano 30B A3B uses a hybrid Mamba-2 plus Mixture-of-Experts design with 30 billion total parameters but only about 3.5 billion active per token, which is the key to its efficiency claims. It was trained by NVIDIA and is distributed openly, with the model collection published on Hugging Face, and it supports English, German, Spanish, French, Italian, and Japanese. The combination of open weights, a sparse active-parameter footprint, and explicit agentic tuning makes it a practical fit for teams that want a self-hostable reasoning model for tool-using assistants, workflow automation, and high-volume inference where operating cost matters more than raw frontier scale.