Nemotron

Nemotron is NVIDIA's family of open large language models, released under permissive licenses for commercial and research use. Unlike most AI labs that train foundation models from scratch, NVIDIA's Nemotron strategy has largely centered on taking open-weight base models -- particularly Meta's Llama series -- and applying NVIDIA's training expertise, hardware, and alignment techniques to produce models optimized for reasoning, instruction following, and agentic tasks.

The family spans several generations. Nemotron-4 340B (2024) was one of NVIDIA's first large-scale releases, a fully internally trained model targeting enterprise use cases. Llama-3.1-Nemotron-Ultra-253B followed as a fine-tuned derivative of Llama 3.1, positioning itself as a frontier reasoning model. Nemotron Super 49B targeted efficient deployment with strong performance at lower serving cost.

Nemotron 3 Super (March 2026) represents the most significant architectural departure, introducing a hybrid mixture-of-experts design that combines Mamba state-space layers with transformer attention, alongside NVIDIA's Latent MoE technique. The result is 120 billion total parameters with only 12 billion active at inference -- frontier capability at a fraction of the compute cost.

NVIDIA's motivation for the Nemotron line is strategic as much as technical. As the dominant supplier of AI training and inference hardware, NVIDIA benefits from a healthy open-weight model ecosystem -- more developers building with open models means more demand for NVIDIA GPUs. Releasing capable open models aligned with NVIDIA's own hardware optimizations (CUDA, NVFP4, Blackwell) creates a flywheel that reinforces the company's infrastructure position.