For context on the Millennium prizes: https://en.wikipedia.org/wiki/Millennium_Prize_Problems

The Millennium Prize Problems are seven well-known complex mathematical problems selected by the Clay Mathematics Institute in 2000. The Clay Institute has pledged to pay one million US dollars for the first correct solution to each problem.

As of 2026, the only Millennium Prize problems to have been solved are the Poincaré conjecture and Navier–Stokes existence and smoothness.^[1] The Clay Institute awarded the monetary prize to Russian mathematician Grigori Perelman in 2010. However, he declined the award because it was not also offered to Richard S. Hamilton, upon whose work Perelman built.^[2] OpenAI declined to claim the Millennium Prize for the Navier-Stokes result.^[1]

Their reluctance to claim the prize may be related to ongoing controversy regarding whether they used information from private chats that a human mathematician trying to solve the problem was having with ChatGPT.

ChatGPT has this to say on their blog:

Our effort began on September 1st after hearing a rumor which we later realized was related to Levent Alpöge, an Anthropic employee, and Tristan Buckmaster, a math professor at NYU. After the completion of our full project and Lean verification (on September 6th), believing from the rumor they also had a solution of Navier–Stokes, we reached out to them to offer a concurrent release of our result and to recognize their priority in a joint announcement. At that point we found out that they had a resolution of the forced Euler problem. In these discussions we offered them visibility into all of the prompts we used and later to see the proof. We recognize the priority of their work on forced Euler and congratulate them on their remarkable mathematical achievement.

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).

Tristan Buckmaster, on Mastodon, is doubtful about this... https://mastodon.social/@tristanbuckmaster/117233413705701198

"I asked when the first prompt had been sent by them. This question was not answered directly by OpenAI for some time. Eventually it was agreed that it had been sent in the past few days, after information about our work had reached OpenAI.

I asked whether the model had been trained on, or had access to, our sessions in Codex, into which we had been putting all our drafts for the whole of this project. I was told the model did not look up user data. I asked again, about training, and I did not get an answer."

I guess this is a good reminder that whatever you type into your favorite's LLM website is not yours anymore.

All that being said, it's a pretty damn big achievement. Mathematically.
From an application point of view, this is not really a relevant regime.