10 million downloads and counting for NVIDIA Cosmos models on @huggingface. 🤗
This milestone belongs to the developers and researchers using open world foundation models to build robots, autonomous vehicles and other physical AI systems.
Thank you for downloading, experimenting, and building with us. 💚
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We tested Nemotron 3 Ultra on agentic chip design.
The task is RTL coding: a model iteratively writes the code that defines a chip's logic, runs it through a simulator, reads the failures, and rewrites.
Across nine categories of real design work, Nemotron 3 Ultra averaged a 97.1% pass rate at 6,629 tokens per iteration, best of the open models tested on both.
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Congratulations to the students who competed at the International Mathematical Olympiad (IMO) 2026. 👏
We put Nemotron 3 Ultra to the test to take on the same problems in the same time limit, with no internet or external tools.
The IMO team graded its solutions 30/42, above the 29-point gold threshold. 🥇
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Devin Outposts are now available on NVIDIA Brev.
Write and profile kernels, run experiments, serve and fine-tune OSS models, and test against real hardware.
Try it out:
Introducing Devin Outposts: run Devin on any machine.
Your Mac mini, a GPU box in your lab, a VM inside your private network, or a Kubernetes cluster next to your internal services.
Tune the Harness, Before Tuning the Model with LangChain | Nemotron Labs
Congrats to the @poolsideai team on their latest release, Laguna S 2.1.
It’s open-weight, delivers way beyond its size, runs great locally and you can customize it with NVIDIA NeMo.
Go try it out on @OpenRouter or download from @huggingface 👉
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Today we're releasing Laguna S 2.1, our most capable model to date.
It's a 118B total parameter Mixture-of-Experts model with 8B activated per token, a context window of up to 1M tokens, and thinking and no-thinking modes.
Capable enough to hold its own against models many times its size. Small enough to run on a single @NVIDIAAI DGX Spark.
Laguna S 2.1 is fully open under OpenMDW-1.1, with weights available today on @huggingface
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NVIDIA Blackwell Ultra just set a world record for pre-training DeepSeek-V3 671B, achieving 1,648 TFLOPs per GPU.
This is about 3x the earlier delivered performance of the previous generation, and is a result of our extreme co-design and continuous software optimization across popular frameworks including Megatron-Core, TorchTitan, and JAX.
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Excited to share: NVIDIA Cosmos 3 Edge is openly available, bringing frontier world models to NVIDIA Jetson Thor and other local devices for physical AI.
Read the blog:
Learn more about it at today’s SIGGRAPH keynote—in person or via livestream at 3:45 p.m. PT:
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NVIDIA is advancing graphics and simulation with agentic and physical AI at #SIGGRAPH2026#.
From open models to real-time simulation, AI and graphics breakthroughs are transforming media, content creation, and robotics.
Read the latest announcements. 👇
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Introducing Cosmos 3 Edge: our open frontier world model built to run on-device.
Cosmos 3 Edge helps robots learn and act, autonomous vehicles understand road scenes and predict intent, and vision AI agents reason across live video for smart infrastructure.
With 4B parameters and a 2B Nemotron-based reasoner, you can run it on DGX Spark, NVIDIA Jetson, and more.
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We evaluated Nemotron-3-Embed from @NVIDIAAI for our @mem0ai memory retrieval pipeline
Tested on longmemeval: retrieval@10 improved from 78.71 to 80.38 over qwen-3-600m
A few things made it a good fit for how we operate: open weights, NVFP4 support on Blackwell for efficient inference, and strong throughput, which matters for a system where writes happen constantly.
A breakdown on how Mem0 uses embeddings and Nemotron-3-embed evaluation below👇
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NVIDIA’s ARDY is a glimpse of where AI animation is heading: real time, open source and you can play with it right now on @huggingface Spaces
Type what the character should do and generate a motion sequence in seconds. Give a sentence a body.
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Another leaderboard win for Nemotron 3 Embed 👀
The 8B model takes #1# on LMEB, with the 1B model right behind it at #2#.
LMEB tests whether embedding models can find the right details across long-running conversations and other memory-heavy tasks, useful for agents that need to remember context across sessions.
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Today we released Nemotron 3 Embed 8B and it reached #1# overall on RTEB 🏆
RTEB benchmarks retrieval accuracy across real-world tasks. Better retrieval gives agents more relevant context, helping improve response accuracy.
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Post-Train NVIDIA Cosmos 3 In a Day with NVIDIA TAO Agent Skills | Cosmos Labs
Today we released Nemotron 3 Embed 8B and it reached #1# overall on RTEB 🏆
RTEB benchmarks retrieval accuracy across real-world tasks. Better retrieval gives agents more relevant context, helping improve response accuracy.
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Red Hat AI just shipped DFlash speculator checkpoints for two of @NVIDIAAI's most powerful open models:
→ Nemotron Ultra 550B
→ Nemotron Super 120B
On math and reasoning: ~5 out of 7 draft tokens accepted on average. On code (HumanEval): ~3.4 out of 7.
Both checkpoints trained with the open source Speculators library from @vllm_project. Apache 2.0. Validated on NVIDIA B200.
One flag to enable in vLLM:
--spec-model RedHatAI/NVIDIA-Nemotron-3-Ultra-550B-A55B-speculator.dflash --spec-tokens 7 --spec-method dflash
🔗 Ultra 550B:
🔗 Super 120B:
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For our Accelerated Business Hackathon with @NVIDIAAI and @stripe, we asked builders to make agents that can earn, spend, and run real operations at any scale.
We judged 292 excellent submissions alongside NVIDIA and Stripe, and now have our winners.
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Congrats @thinkymachines on the new open model 🙌
Inkling was trained on NVIDIA GB300 NVL72 and the NVFP4 checkpoint is available today on @huggingface:
Happy building!
and the 🦞group pic. Huge thank you to everyone who joined us!
First stop in Japan: Build-a-Claw. 🇯🇵
Jensen made a surprise stop in the heart of Tokyo to meet with devs, give away some DGX Sparks, and see what they're building with open models.
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