nemotron

NVIDIA has released over 10 trillion pre-training tokens and millions of post-training samples as part of its Nemotron open data initiative for building AI agents. The release includes the Nemotron Post-Training v3 Prompt Atlas, an interactive visualization tool, and Nemotron-Personas dataset representing 2.4 billion people across 10 countries.

NVIDIA released Nemotron-3-Ultra-550B-A55B-NVFP4, a 550B parameter model with 55B active parameters, featuring a 1M token context window and configurable reasoning mode. The model uses a hybrid LatentMoE architecture combining Mamba-2, Mixture-of-Experts, and Attention layers with Multi-Token Prediction, trained with NVIDIA's NVFP4 quantization-aware approach.

NVIDIA released Nemotron-3-Ultra-550B, a frontier-scale model with 550B total parameters (55B active) and up to 1M token context window. The model uses a hybrid LatentMoE architecture combining Mamba-2, MoE, and attention layers with Multi-Token Prediction, trained with NVFP4 quantization-aware methods from December 2025 to April 2026.

NVIDIA demonstrated that task-seeded synthetic Q&A data improves model performance across multiple benchmarks in a 100B-token continuation experiment on Nemotron-3 Nano. The approach improved GPQA scores by +11.1 points, MMLU-Pro by +1.8, average code by +1.9, and commonsense understanding by +1.6.

Nvidia will invest $26 billion over the next five years to build open-weight AI models, according to a 2025 financial filing confirmed by executives. The move signals a strategic shift from chipmaker to AI frontier lab, with the company releasing Nemotron 3 Super (128B parameters) and claiming it outperforms GPT-OSS on multiple benchmarks.

Amazon Bedrock now offers NVIDIA's Nemotron 3 Nano as a fully managed serverless model, expanding its Nemotron portfolio alongside previously available Nemotron 2 Nano 9B and Nemotron 2 Nano VL 12B variants. The addition enables developers to deploy NVIDIA's smallest inference-optimized model without managing infrastructure.