Nvidia Nemotron 3 Family of Models

Summary

Models Nemotron 3 White Paper Nano Tech Report We announce NVIDIA Nemotron 3, the most efficient family of open models with leading accuracy for agentic AI applications. The Nemotron 3 family consists of three models: Nano, Super, and Ultra. These models deliver strong agentic, reasoning, and conversational capabilities. 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. We are releasing the Nemotron 3 Nano model and technical report. Super and Ultra releases will follow in the coming months. Nemotron 3 technologies Hybrid MoE: Nemotron 3 family of models utilize a hybrid Mamba-Transformer MoE architecture to provide best-in-class throughput while having better or on-par accuracy than standard Transformers. LatentMoE: Super and Ultra utilize Latent MoE, a novel hardware-aware expert design for improved accuracy. Multi-Token Prediction: Super and Ultra incorporate MTP layers for improved long-form text generation efficiency and better model quality. NVFP4: Super and Ultra are trained with NVFP4. Long Context: Nemotron 3 models support context length up to 1M tokens. Multi-environment Reinforcement Learning Post-training: Nemotron 3 models are trained using a diverse set of RL environments helping models achieve superior accuracy across a broad range of tasks. Granular Reasoning Budget Control at Inference Time: Nemotron 3 models are trained to work with inference-time budget control. Nemotron 3 Nano Nemotron 3 Nano is a 3.2B active (3.6B with embeddings), 31.6B total parameter model. It achieves better accuracy than our previous generation Nemotron 2 Nano while activating less than half of the parameters per forward pass. Key highlights: More accurate than GPT-OSS-20B and Qwen3-30B-A3B-Thinking-2507 on popular ...