Today we're shipping Nemotron 3 Ultra.
A 550B MoE frontier-intelligence open model built for long-running agents.
It delivers 5x faster inference and lowers the cost of complex agentic tasks by up to 30% versus other open frontier models.
🎉 Congrats to @NVIDIAAI on Nemotron 3 Nano Omni — a 30B hybrid Transformer-Mamba MoE (3B active) that unifies vision, audio, video, and text in a single reasoning loop. 256K context, FP8 / NVFP4 quantization, open weights.
Day-0 support in vLLM — tool calling, reasoning, and efficient video sampling for long-video workloads, verified on NVIDIA GPUs.
🔗 https://t.co/95VhKtDLqw
🔗 https://t.co/i8r6VHjVAK
NVIDIA Nemotron™ 3 Nano Omni is live on OpenRouter.
An open 30B-A3B multimodal model for agentic workflows: text, image, video, and audio in → text out, with a 256k context window and efficient MoE architecture for computer use, documents, and AV reasoning.
Today we're releasing Nemotron 3 Nano Omni.
Audio, Video, Image, Text ➡️ Text
Ask questions about all your data.
Amazing efficiency powered by the Nemotron Hybrid SSM MoE architecture.
State of the art multimodal intelligence.
Nemotron 3 Nano Omni is out: an open-source Omni model built for strong accuracy, broad capabilities, and speed.
- weights https://t.co/jl3X5OD7E5
- tech report https://t.co/4FY6cEPJBO
The articles from #GTC19... amazing! @WalmartLabs uses @NVIDIA#GPU and @RAPIDSai to save millions in wasted goods! I'm so proud of the team, and beyond excited for what's coming next. This is just the beginning! https://t.co/UWnuvSXVoO
"I'm doing a (free) operating system (just a hobby, won't be big and professional like gnu)”
Linus Torvalds, a 21 year old student at University of Helsinki, announces on Usenet that he is working on a new OS that would eventually become Linux
Take a look inside NVIDIA's AI training and validation infrastructure for autonomous driving with MagLev, introduced today at @FB#AtScale#AI#autonomousvehicles https://t.co/Vw1tExZQ2n
#Python news: Guido accepted PEP 572. Python now has assignment expressions.
if (match := https://t.co/wHiX17iPKu(data)) is not None:
print(https://t.co/mviw1VeMnU(1))
filtered_data = [y for x in data if (y := f(x)) is not None]
https://t.co/BfCDRi8ZK6
Very excited about our work on active learning. For problems where raw data is much larger than what you can effectively label, active learning is key to label the right data. https://t.co/B72hutnlbk