Karan Sapra

Principal Research Scientist @Nvidia for Nemotron VLMs.
Gamer in spare time.

[Bryan Catanzaro @ctnzr]

Nemotron 3.5 Lightning:
Same architecture as 3.0 Nano,
with added speculative decoding, and with the intelligence of 3.0 Super.

⚡️⚡️⚡️

[Jensen Huang @JensenHuang]

For my first post, I’m sharing a letter @NVIDIA signed on why open models matter.

AI will transform every industry, power every company, and be built by every country.

Open models strengthen safety and cybersecurity, accelerate innovation and diffusion, and enable sovereignty.

The world needs both frontier closed models and frontier open models.

https://t.co/AUKzoQ5Ikb

[Bryan Catanzaro @ctnzr]

NVIDIA Nemotron 3 Ultra is now live!

Frontier accuracy, 5X greater speed, 30% lower cost.

Deploy however you need - on-premise, on the cloud, or at the edge.

Model is live on HuggingFace under the OpenMDW 1.1 license.

https://t.co/IOfAwv3jB6

[NVIDIA AI @NVIDIAAI]

Nemotron 3 Ultra is coming this week. ⌛️

[Bryan Catanzaro @ctnzr]

Nemotron 3 Ultra:

Frontier smart.
5X faster.
30% cheaper.

💚💚💚

[Bryan Catanzaro @ctnzr]

Some awesome open models trending on HF right now, including models from @deepseek_ai, @Xiaomi, @OpenAI, @MistralAI, and @aipoolside.

And of course Nemotron 3 Nano Omni from @NVIDIAAI

So great to see!

[Georgia Channing @cgeorgiaw]

🤗🤗🤗introducing Hugging Science -- the home of AI for science 🤗🤗🤗

open models and datasets are the powerhouse of science (see the PDB), but finding the models and data you actually need for your breakthrough is hard af

you shouldn't need to scrape arxiv, own your own wetlab, fight a custom HDF5 parser, build a fusion stellarator, and beg for compute before you've trained a single epoch

so we're changing that

we've put all the best science on @huggingface in one place:
- 78GB of genomics data
- 11TB of PDE simulations
- 100M cell profiles
- 9T DNA base pairs
- 13M molecular trajectories
- 400k medical QA pairs

and much more, all open, and all ready for training (+ you can also now filter and search by domain, task, and keyword)

we've put together all the biggest releases from our partners at NASA, Google, OpenAI, Meta FAIR, Arc Institute, Ginkgo, SandboxAQ, Proxima Fusion, NVIDIA, Ai2, OpenADMET, InstaDeep, Future House, Polymathic AI, LeMaterial, Earth Species Project, Merck, and Eve Bio

if you're not sure where you fit in -- work on open challenges for problems that matter: including fusion stellarator design, ADMET, antibody developability, multilingual medicine, catalysis and materials, and scientific reasoning.

we're already changing how science gets done:

a fusion startup needed a benchmark for stellarator plasma confinement that didn't exist. @proximafusion shipped ConStellaration on Hugging Science: a leaderboard, dataset, and eval metrics, all in one place.

a drug discovery team wanted to predict hPXR induction. OpenADMET put up a blind challenge: 11,000+ compounds assayed at Octant, 513 held out, two tracks (pEC50 + structure). Anyone in the world can train and submit.

an antibody team at @Ginkgo released GDPa1, a developability dataset for stability, manufacturability, and immunogenicity prediction, with a live leaderboard scoring every submission.

if you know a problem the ML community should be working on, let us know. make a challenge! this is about putting all the tools for solving science in one place. so we can hillclimb!

→ https://t.co/T4l4r1lDz0

[vLLM @vllm_project]

🎉 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

[Maarten Van Segbroeck @mvansegb]

Nemotron 3 Nano Omni shipped. The long-doc reasoning is real - and synthetic data did a lot of the heavy lifting.

Proud of the NeMo Data Designer team's contribution. Full SDG story in the dev note👇

🔗 https://t.co/oA0GJA3EqD

[Piotr Żelasko @PiotrZelasko]

Today we released Nemotron-3-Nano-Omni-30B-A3B - our first Omni model, with speech and audio understanding capabilities powered by parakeet-tdt-0.6b-v2 encoder.
🫡1st position on VoiceBench
🌏English only
🎙️5.95% WER on Open ASR Leaderboard
📽️Video+audio understanding

[Bryan Catanzaro @ctnzr]

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.

[NVIDIA @nvidia]

https://t.co/Ow621ET16t

[Wei Ping @_weiping]

🚀 Introducing Nemotron-Cascade 2 🚀

Just 3 months after Nemotron-Cascade 1, we’re releasing Nemotron-Cascade 2: an open 30B MoE with 3B active parameters, delivering best-in-class reasoning and strong agentic capabilities.

🥇 Gold Medal-level performance on IMO 2025, IOI 2025, and ICPC World Finals 2025:
• Capabilities once thought achievable only by frontier proprietary models (e.g. Gemini Deep Think) or frontier-scale open models (i.e. DeepSeek-V3.2-Speciale-671B-A37B).
• Remarkably high intelligence density with 20× fewer parameters.

🏆 Best-in-class across math, code reasoning, alignment, and instruction following:
• Outperforms the latest Qwen3.5-35B-A3B (2026-02-24) and even larger Qwen3.5-122B-A10B (2026-03-11).

🧠 Powered by Cascade RL + multi-domain on-policy distillation:
• Significantly expand Cascade RL across a much broader range of reasoning and agentic domains than Nemotron-Cascade 1, while distilling from the strongest intermediate teacher models throughout training to recover regressions and sustain gains.

🤗 Model + SFT + RL data:
👉 https://t.co/4QJqfTOt6I

📄 Technical report:
👉 https://t.co/dFC00m6RZU

[NVIDIA AI Developer @NVIDIAAIDev]

Ask the Experts: Meet Nemotron Parse AI Researchers | Nemotron Labs https://t.co/owi2UUgyED

[Andrew White 🐦‍⬛ @andrewwhite01]

Here's a detailed write-up of how we used Nemotron-Parse to extract images/tables/equations from research papers while making PaperQA3. Thanks to the NVIDIA team! They were really helpful for getting us from prototype to scale of 100s of pages/s.

https://t.co/Pm3tyX1GF2

[NVIDIA AI Developer @NVIDIAAIDev]

4 million downloads and counting—what a journey 👏

Thank you for building, experimenting, and sharing what Llama Nemotron Nano VL can do.

[Andi Marafioti @andimarafioti]

Just dropped: 🎉 NVIDIA Nemotron-Parse v1.1
Next-gen OCR for parsing PDFs & PPTs into structured, machine-ready output (text + bounding boxes + semantic classes).
Ready for commercial use and to generate datasets🚀
Check the examples on Hugging face! https://t.co/pfOz13AQCz

[hardmaru @hardmaru]

This #StableDiffusion add-on for Blender looks amazing. @AI_Render renders an AI-generated image based on a text prompt and your scene in Blender.

https://t.co/v3IvXBkcpi

[NVIDIA GeForce @NVIDIAGeForce]

Experience the critically-acclaimed FPS, Bright Memory: Infinite enhanced with NVIDIA DLSS 3, delivering 2X+ faster performance.

Available Now → https://t.co/28gY7hMZ06

[Karan Sapra @currenator]

https://t.co/9tTTXCsmti