NVIDIA model releases

NVIDIA's efficient open Mixture-of-Experts model, released Aug 11 2026 for long-running agents. A hybrid Mamba-2 + MoE + Attention design with ~31.6B total and ~3.6B active parameters and a 1M-token context, shipped alongside the NeMo Switchyard model router. NVIDIA reports performance comparable to gpt-oss-120b at roughly a quarter of the total parameters, up to 4x the output speed of similar-sized models, and 10,000 tasks completed ~30% faster than Qwen3.6-35B at similar accuracy. Vendor-reported BF16 figures: SWE-bench Verified 51.56, GPQA Diamond 75.44, MMLU Pro 81.94, PinchBench 85.37 — self-reported and unverified by an independent harness at launch. Ships under the permissive OpenMDW-1.1 license with weights, training data, and recipes released, and is available on Hugging Face, ModelScope, OpenRouter, and build.nvidia.com as an NVIDIA NIM microservice.

A deployment-optimized open-weight model from NVIDIA, released July 6, 2026 — a compressed variant of Nemotron-3-Super-120B-A12B produced with "Iterative Puzzle", a post-training compression framework that jointly prunes MoE experts, active-parameter budget, and Mamba state to boost inference efficiency while preserving accuracy. Reduces the parent from 120.7B total / 12.8B active to 75.3B total / 9.3B active, keeping the hybrid Mamba-Transformer LatentMoE architecture with Multi-Token Prediction. Delivers ~2x higher server throughput than Nemotron-3-Super on a single 8xB200 node at matched user throughput and raises sustainable 1M-token single-H100 concurrency from 1 to 8 requests. Targets collaborative agents, chatbots, RAG, complex instruction-following, and long-context reasoning across English, code, and six other languages. Shipped in BF16, FP8, and NVFP4 variants under the OpenMDW-1.1 license.

NVIDIA's largest Nemotron 3 open-weight hybrid Mamba-Transformer MoE, tuned for agentic reasoning, coding, planning, and tool calling.

Open-weight hybrid Mamba-Transformer MoE designed for collaborative agents and high-volume enterprise workflows.

Efficient Nemotron 3 MoE checkpoint for agentic reasoning and coding, activating about 3B parameters while supporting 1M-token contexts.

Open Llama Nemotron reasoning model from NVIDIA's 2025 Nemotron family.

NVIDIA-tuned Llama 3.1 70B instruction model optimized with Nemotron reward and alignment recipes.

NVIDIA's large open model family for synthetic data generation and reward modeling.