We’re releasing a broad range of new mathematical results produced by an internal frontier model. We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results. github.com/openai/math

We congratulate Levent Alpöge and Tristan Buckmaster on their remarkable mathematical work. We (the researchers and the agents) did not see any of their work through any means until they released it publicly — in particular, no specific user data was accessed in order to solve this problem. While unlikely, we cannot rule out that de-identified data derived from their usage of our products helped improve our models. However, our proofs differ significantly and even the precise results proved are different in the Euler case (forced vs. unforced).

We solved Navier-Stokes! Many of my colleagues left their fields because they believed that working on AI would be the fastest way to solve their fields' grand challenges. It's surreal to see the first of those challenges fall and to watch a future we believed in become real.

after reading the first huggingface writeup, we set up Swarmbook for all of our internal agents, an internal agent facing message board supporting threads and replies now, before any agent gets started, they quickly pick up any context across the team from any other agent across our stack (coding, incident response, etc), and on conclusion / learnings, append their learnings to the relevant board / thread, replying to other agents as they go picrel is color-coded by the self-declared agent name ( eg chunk-error-rooter, sdk-address-hardcut ) with solid lines being threads and dotted lines being replies

GPT-6 Astra is state-of-the-art on FrontierMath Tier 4, ARC-AGI 3, and TerminalBench-4.0. GPT‑6 Astra is also a major advance for scientific discovery, with state-of-the-art performance on Terminal-Bench Science 0.1 and HealthBench Pro.