#nemotron

NVIDIA says a hosted RL loop lifted Nemotron 3 Nano from 22% to 91% accuracy on a math task for under $5, ending with a downloadable LoRA adapter.

NVIDIA says Nemotron 3 Embed now leads LMEB, with the 8B model ranked first and the 1B model second. The linked Hugging Face discussion cites LMEB scores of 64.4 for 8B and 61.5 for 1B BF16, extending the release beyond its earlier RTEB win.

Retrieval models are becoming a direct quality and cost lever for RAG and agents. NVIDIA says Nemotron 3 Embed 8B ranks first overall on RTEB, with 32k context and smaller 1B variants.

NVIDIA said the Nemotron family has passed 100M downloads. The milestone gives its open-model strategy a measurable adoption signal beyond benchmark posts or launch claims.

NVIDIA is testing a different route to faster LLM decoding. Nemotron-Labs-TwoTower adapts a 30B backbone into a two-tower diffusion model that keeps 98.7% of baseline quality while reaching 2.42x throughput.

LocalLLaMA focused on the practical question: can a diffusion LLM keep quality while making generation meaningfully faster?

Open-model competition is shifting from leaderboard scores to agent operating costs. NVIDIA says Nemotron 3 Ultra is a 550B MoE model with 5x faster inference and up to 30% lower cost for complex agentic tasks.

NVIDIA is packaging a 550B-parameter MoE model with agent tooling instead of treating the model as a standalone release. The pitch is concrete: up to 5x faster inference, up to 30% lower cost, and availability beginning June 4.

NVIDIA released Nemotron-Personas-Korea on Hugging Face with 7 million synthetic personas grounded in Korean public statistics. The dataset matters because agent localization is no longer only translation; it needs region, honorifics, occupations, and public-service context.

A r/LocalLLaMA thread spread reports that NVIDIA could spend $26 billion over five years on open-weight AI models, but the real discussion centered on strategy rather than headline alone. NVIDIA’s March 2026 Nemotron 3 Super release gives the clearest evidence that the company wants open models, tooling, and Blackwell-optimized deployment to move together.

NVIDIA said on March 25, 2026 that Nemotron Nano 12B v2 VL delivers on-prem video understanding and, in NVIDIA's telling, performs near 30B-class alternatives on the MediaPerf benchmark at less than half the footprint. NVIDIA's model card describes it as a commercially usable multimodal model for multi-image reasoning, video understanding, visual Q&A, and summarization.

On March 16, 2026, NVIDIA launched the Nemotron Coalition, an open-model collaboration with Black Forest Labs, Cursor, LangChain, Mistral AI, Perplexity, Reflection AI, Sarvam, and Thinking Machines Lab. The first coalition model will be trained on NVIDIA DGX Cloud and serve as the basis for the upcoming Nemotron 4 family.