Nemotron 3 Nano 30B A3B

Nemotron 3 Nano 30B A3B is a compact open-weight language model built around a hybrid Mixture-of-Experts architecture combined with Mamba-2, a state-space foundation that enables linear-time sequence modeling. This design means only a fraction of the model's parameters are active for any given token, delivering significantly higher throughput and lower inference costs than dense 30B models while maintaining strong accuracy. The model was engineered from the ground up to handle agentic workloads, coding tasks, and mathematical reasoning, positioning it as a practical backbone for developers building specialized AI systems that need both speed and precision.

NVIDIA trained this model from scratch and made it fully open by releasing the model weights, training datasets, and complete training recipes. This transparency allows developers to customize, optimize, and deploy the model on their own infrastructure, which is especially valuable for applications where data privacy and security are priorities. The combination of open weights, a massive context window, and efficient MoE inference makes Nemotron 3 Nano 30B A3B well-suited for long-context agent workflows, deep reasoning tasks, and high-throughput production systems where running large models locally or in private cloud environments is desirable.