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NVIDIA Debuts Nemotron 3 Family of Open Models | NVIDIA Newsroom https://nvidianews.nvidia.com/news/nvidia-debuts-nemotron-3-family-of-open-models
@OpenAI Super cool to see the eval on the Hugging Face hub too – OPEN SOURCE EVALS FTW! 🔥 https://x.com/reach_vb/status/2000982838171328882
.@nvidia Nemotron 3 Nano is now available on Ollama! Local ollama run nemotron-3-nano Cloud ollama run nemotron-3-nano:30b-cloud https://x.com/ollama/status/2000820163231232167
🚀 Day-0 support for @NVIDIA Nemotron 3 Nano in SGLang SGLang now supports Nemotron 3 Nano on Day 0 🎉 A highly efficient, fully open Hybrid MoE model with 1M context, thinking budget, and industry-leading accuracy per compute. ✅ Open weights, data, and recipes ⚡ Fast, https://x.com/lmsysorg/status/2000567938949243111
As AI Grows More Complex, Model Builders Rely on NVIDIA | NVIDIA Blog https://blogs.nvidia.com/blog/leading-models-nvidia/
BREAKING CUDA MOAT EXPANDS: Today, NVIDIA has acquired SchedMD, makers of SLURM, a widely used “”open source”” workload scheduler. Many AI companies such as Mistral, Thinking Machines, parts of Meta’s FAIR division, university academic labs use SLURM. NVIDIA’s acquisition expands https://x.com/SemiAnalysis_/status/2000620209262985641
BREAKING: NVIDIA just dropped an open 30B model that beats GPT-OSS and Qwen3-30B — and runs 2.2-3.3× faster Nemotron 3 Nano: • Up to 1M-token context • MoE: 31.6B total params, 3.6B active • Best-in-class performance for SWE-Bench • Open weights + training recipe + https://x.com/AskPerplexity/status/2000589984818954719
First time I see a major org release @huggingface collections inside collections 🤯 Kudos @nvidia for this brilliant release https://x.com/NielsRogge/status/2000639749514760465
In collaboration with NVIDIA, the new Nemotron 3 Nano model is fully supported in llama.cpp Nemotron 3 Nano features an efficient hybrid, Mamba, MoE architecture. It’s a promising model, suitable for local AI applications on mid-range hardware. The large context window makes it”” / X https://x.com/ggerganov/status/2000574990425415765
Inside NVIDIA Nemotron 3: Techniques, Tools, and Data That Make It Efficient and Accurate | NVIDIA Technical Blog https://developer.nvidia.com/blog/inside-nvidia-nemotron-3-techniques-tools-and-data-that-make-it-efficient-and-accurate/
New mlx-lm release: pip install -U mlx-lm Includes support for a few new models: – Nemotron 3 Nano (Nvidia) – Devstral (Mistral) – rnj-1 (Essential AI) https://x.com/awnihannun/status/2000974327660077298
Nvidia continues to put out some of the strongest and fastest open models. Pretraining and post training data are released as well, something very few orgs have done”” / X https://x.com/tri_dao/status/2000707760288092655
NVIDIA Debuts Nemotron 3 Family of Open Models | NVIDIA Newsroom https://nvidianews.nvidia.com/news/nvidia-debuts-nemotron-3-family-of-open-models/?ncid=so-twit-561360
NVIDIA has just released Nemotron 3 Nano, a ~30B MoE model that scores 52 on the Artificial Analysis Intelligence Index with just ~3B active parameters Hybrid Mamba-Transformer architecture: Nemotron 3 Nano combines the hybrid Mamba-Transformer approach @NVIDIAAI has used on https://x.com/ArtificialAnlys/status/2000602570092675402
NVIDIA just released Nemotron-Agentic-v1 on Hugging Face This dataset empowers LLMs as interactive, tool-using agents for multi-turn conversations and reliable task completion. Ready for commercial use. https://x.com/HuggingPapers/status/2000628009049760072
NVIDIA just released Nemotron-Cascade-8B on Hugging Face A powerful 8B general-purpose reasoning model that achieves best-in-class performance across diverse benchmarks, from math to coding, by using novel Cascade RL. https://x.com/HuggingPapers/status/2001065870676603333
NVIDIA releases Nemotron 3 Nano, a new 30B hybrid reasoning model! 🔥 Nemotron 3 has a 1M context window and the best in class performance for SWE-Bench, reasoning and chat. Run the MoE model locally with 24GB RAM. Guide: https://x.com/UnslothAI/status/2000568378407452746
Really impressive release from NVIDIA, who not only went head-to-head with Qwen3, but: – innovated on the architecture (risky for most open labs) – did legit multi-env RL, complete with agentic evals (first time I see this from an open lab) – plan to open source the pretraining”” / X https://x.com/_lewtun/status/2000599470099099990
SemiAnalysis InferenceMAX showing GPT OSS on Blackwell is 33% more tokens per $ in just 1 month thanks to the awesome work of @vllm_project and @nvidia”” / X https://x.com/dylan522p/status/2002135815233970295
This is not just another strong open model. Nemotron actually releases training data (!), RL environments, and training code. This is a big difference: almost all model developers just want people to use their models; NVIDIA is enabling people to make their own models. We are”” / X https://x.com/percyliang/status/2000608134205985169
Today, @NVIDIA is launching the open Nemotron 3 model family, starting with Nano (30B-3A), which pushes the frontier of accuracy and inference efficiency with a novel hybrid SSM Mixture of Experts architecture. Super and Ultra are coming in the next few months. https://x.com/ctnzr/status/2000567572065091791
vLLM delivers even more inference performance with the same GPU platform. In just 1 month, we’ve worked with NVIDIA to increase @nvidia Blackwell maximum throughput per GPU by up to 33% — significantly reducing cost per token — while also enabling even higher peak speed for https://x.com/vllm_project/status/2001449658984632699
When @NVIDIA announced Nemotron 3 – it marked a symbolic turning point in a year that fundamentally reshaped open-source AI leadership. Is NVIDIA the new open-source king? What’s behind this strategy? Let’s see. ▪️ It releases 3 trillion tokens of new pretraining, 18 million https://x.com/TheTuringPost/status/2001087448299065372
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