OFFICIALLY LAUNCHED
H's computer-use agent API now runs on desktop and web, built for devs and builders. Fully managed, powered by our #1 OSWorld-Verified model.
Just tried NVIDIA Snapshot on a 35B model on a single H100. Boot time went from 7.5 min (cold start from S3) to 46 s restoring from a snapshot 🏎️
Now testing TP>1, since v0.2.0 added support for it ⏳
Online RL is only as fast as its inference.
At GTC Europe, @EmrickSini showed how we made RL steps 24% faster with elastic inference, fast replica booting and smart request routing.
We made online RL for computer-use agents 24% faster with 5% fewer GPU-hours.
At GTC Europe, I shared how we used prime-rl + NVIDIA Dynamo to post-train Nemotron Omni (30B-A3B) at H, with inference capacity that adapts during training🧵
As promised: after SF, Paris 🇫🇷
Computer Use Agents hackathon with @42AI_, November 7-8.
€10K cash prize, credits, more to be announced.
With @gladia_io, @cognition, @Linkup_platform and @stripe.
Apply here: https://t.co/hQRxv1wPJA
Sidequest: we gave Holo4 a pile of bricks and a pile of blocks 🧱
Type an idea and watch it build.
HoloBricks makes brick models. HoloBlocks makes worlds you can walk around in.
Both built on our Agents API and open source.
Code and demos below ⬇️
Have a play: https://t.co/ASnzMCzc22
Both apps are open source, built with our TypeScript SDK and Agents API.
Fork them, add your own tools, share your weirdest build and tag us!
🧱 HoloBricks: https://t.co/GBMS8Za0uK
🌍 HoloBlocks: https://t.co/vutFIFhsxc
How it works: write code → run → look → revise.
Holo4 writes Python, runs it, checks renders from several angles, then makes changes.
Your browser’s GPU renders the build. A custom “look” tool sends the images back to the agent
Start with “a house held up by balloons.”
Then push it: bigger roof, twice the balloons, a dog on the porch.
You can steer while it builds, or select part of the model and ask for a change right there
Live with @NVIDIAAI this Thursday: how we serve vision-language models for computer-use agents.
Thu Oct 8 · 1PM CEST / 7AM ET
With @AvshalomM (inference team lead) and @EmrickSini (research engineer). Live Q&A.
SF Tech Week is next week. @tonywu_71 picked his favorites 👇
MongoDB hackathon, Boba & Build Night, no-cloud AI with ZETIC × Liquid, Physical AI Happy Hour, World Models & GPUs Coffee.
Oct 8: we're co-hosting the @skypilot_org AI Infra Meetup.
What are your picks?
Training computer-use agents means running thousands of environments next to the trainer, with sub-second cold starts so the GPUs never wait.
We do it on @skypilot_org.
On Oct 8, Leonard Benedetti, core researcher at H, will walk through how we train, how we eval, and what actually breaks when you scale up.
Finally, we are releasing the trajectories behind our public benchmark results so they can be inspected and replayed:
- Replay them at https://t.co/92MQ2QtnC4
- Download them from https://t.co/Bmc4bOfSOr
Today we're releasing Holo4, our new family of generalist computer-use models.
Holo4 can click, code, and call tools across desktop, web, Android, code sandboxes, MCP servers, and business APIs.
Available today on the H Models API for commercial use.
The training recipe combines supervised fine-tuning with two asynchronous online-RL experts, specialized for different classes of workflows and merged back into one generalist model.