Today, I am hosting a BANGER of a stream with @kuchaev and Tugrul - you can check it out live at @NVIDIAAI at 11AM PT, or on YouTube! We're just going to be answering questions about Nemotron 3 Ultra the whole time - come on down!

Nemotron 3 Ultra is now available for Pro and Max subscribers on Perplexity and Computer. It's @nvidia's new open model built for long-running agents.

🚨 BREAKING: The death toll in Kyiv has risen to 4 with 58 wounded after a massive Russian overnight missile and drone attack, local authorities report.

Introducing NVIDIA Cosmos 3 We released NVIDIA Cosmos 3 last night. And today, seeing it take the top spots across 8 open model leaderboards feels surreal. We spent months working towards this moment. Here’s the breakdown: The Leaderboard Wins World Reasoning 🏆 #1 open model on VANTAGE-Bench for vision AI 🏆 #1 overall on Traffic Anomaly Reasoning (TAR) World Generation 🏆 #1 open model on Artificial Analysis Image-to-Video leaderboard 🏆 #1 open model on Artificial Analysis Text-to-Image leaderboard 🏆 #1 open model on PAI-Bench for physical AI synthetic data generation 🏆 #1 open model on Physics-IQ, which measures accuracy on physical laws 🏆 #1 open model on R-Bench for world generation quality World Action 🏆 #1 on RoboArena for specialized policy 🏆 #1 on RoboLab for action generation But the leaderboards are only part of the story. The real story is why we built Cosmos 3 in the first place. The Problem Training robots and autonomous systems in the real world is painfully hard. Robots need to try the same thing numerous times before they succeed reliably. Self-driving cars need rare edge cases that may never happen naturally. Smart machines need to understand physics, motion, contact, failure, and surprise. And real-world data is slow, expensive, and sometimes dangerous to collect. At some point, the answer cannot just be “collect more data.” You can’t collect your way out of an infinite physical world. You have to generate it. That… was the question behind Cosmos: Can one model understand the physical world deeply enough to reason about it, simulate it, and generate actions inside it? What We Built Cosmos 3 is the first omni-model for physical AI. It can understand and generate across: language · images · video · audio · action sequences It is not just a VLM. Not just a video generator. Not just a robot policy model. It is all of them, in one single model. That matters because physical AI has been fragmented for a long time. Cosmos 3 is our attempt to collapse that fragmentation. Depending on how you configure the inputs and outputs, the same model can act as a vision-language model, a video/world generator, a world simulator, or a world-action model. No separate architecture required. The Architecture Under the hood, Cosmos 3 uses a dual-tower Mixture-of-Transformers architecture. One tower is autoregressive for reasoning. It handles next-token prediction for language and discrete understanding. The other tower is diffusion-based- for generation. It denoises images, video, audio, and action trajectories. Two towers. Dual-stream joint attention. One shared world representation. Each modality gets its own tools: visual encoders, video VAEs, audio VAEs, and action projectors that can map different embodiments into a unified action space. Action is a first-class modality in Cosmos 3. That’s what makes it more than a video model. It doesn’t just predict and generate what the world might look like. It can connect reasoning and world modeling to physically grounded action. Why This Matters One of the most interesting findings from the ablation work is that training action domains together creates positive transfer. That means adding more embodiments does not just add more use cases. It can actually make the model better. This is the heart of why omnimodal training matters. A shared world representation is not just convenient. It can make each individual task stronger. That’s the part that feels like the beginning of something much bigger. The part I’m most excited about is that Cosmos 3 is fully open. Developers get the models, scripts, optimization, inference endpoints, post-training recipes, datasets, and benchmarks. Everything is available under the Linux Foundation’s OpenMDW 1.1 License. You can use Cosmos 3 out of the box. You can use the VLM, world model, or world-action pieces separately. You can post-train it for your own domain, embodiment, or accuracy target. That’s what makes this feel different. Cosmos 3 is not just a model release. It is the foundation for building intelligence for autonomous machines. For me, Cosmos 3 feels like a step toward a world where physical AI development becomes much more scalable and accessible - to a new age of developers and agents. That’s what we built Cosmos 3 for. I cannot wait to see what you build with it. Download Models on Hugging Face huggingface.co/collections/n… Customize Models on GitHub github.com/NVIDIA/cosmos Read the Tech Blog to Learn More developer.nvidia.com/blog/de…

Nemotron 3 Ultra is coming this week. ⌛️

Welcome to the NVIDIA RTX Spark channel. A new superchip for the age of personal AI. Don't worry, your favorite NVIDIA local AI content continues on right here, just with a new headliner. Let's get started...

Welcome to Day 2. Yesterday, we showed the broader work we're doing with the pioneers of continual learning. Today we'd like to deep dive on one: how we post-trained an open model for legal work, in partnership with @Harvey. We've built a platform where production data is the moat. Every correction, retry, and edit becomes signal you can post-train on, and the models are plug and play: customer's can drop in their model of choice, and improve from there. Fields like legal and finance make those demands absolute, with hard security, sovereignty, and provenance requirements. That's why we post-trained @nvidia 's open-weight Nemotron 3 Super, on Harvey's LAB benchmark. The results, in just hours: post-trained Nemotron 3 Super approaches the closed frontier, matches GPT 5.5, lifts rubric-pass criteria 25%, all while beating the performance-vs-cost frontier. That's the power of our platform. And this is just a glimpse towards what the future of intelligence will look like: continual learning, where products get smarter every time they're used. Thanks to @nikogrupen, @gabepereyra, @ItsJulioPereyra, and the whole Harvey team for their collaboration on this. Much more to come soon on continually learning legal agents