Nemotron 3 Nano 30B A3B is an NVIDIA-trained large language model built as a unified system for both reasoning and non-reasoning tasks. Rather than splitting these behaviors across separate checkpoints, the model first generates an internal reasoning trace and then produces a final answer. This design lets a single deployment serve conversational workloads and analytical tasks without swapping models, and a flag in the chat template controls whether the reasoning trace is emitted or suppressed, with a slight accuracy trade-off on harder prompts when reasoning is turned off.
Under the hood, the model uses a hybrid Mixture-of-Experts architecture that interleaves Mamba-2 and MoE layers with attention layers, giving it the throughput benefits of state-space sequence modeling while retaining the long-range modeling strengths of attention. It carries 30B total parameters but only activates around 3.5B per token through its expert routing, which is the source of the A3B designation. NVIDIA has also released ultra-efficient precision variants such as the NVFP4 build, signaling a roadmap toward smaller memory footprints and faster inference on commodity and edge hardware. That combination of open weights, configurable reasoning, and a sparse-active MoE design makes the model a practical fit for teams that want strong reasoning quality without paying the full cost of a dense 30B-parameter deployment.
