OpenAI posts 722 AI-generated math papers on GitHub

OpenAI says the results came from an internal model used to evaluate itself on unsolved research problems, the same model and procedure for most of them. Ten inference summaries were released, covering topics such as the irrationality measure of pi, the Mahler conjecture, the Kaplansky direct finiteness conjecture in characteristic 2, the isomorphism problem for free group factors, spontaneous magnetization of the quantum Heisenberg ferromagnet, and the 3D relativistic Vlasov-Maxwell system.

The publication follows an earlier dispute: in September OpenAI said its internal model solved the Navier-Stokes equation, one of the Millennium Prize problems, and a mathematician working on prior research questioned how it was done. OpenAI then announced a partnership with AGMAI, an independent group of mathematicians, and said the internal model had solved over 100 open problems. In August it said an internal version of its next flagship model, Astra, had produced new results on ten unsolved problems, and in October 2025 an executive's post claiming GPT-5 solved an Erdos problem was deleted after criticism.

AGMAI's September 29 recommendations call for publishing in repositories not controlled by AI companies, disclosing model names, prompts, inference summaries, time and compute costs, Lean formalization, and the number of unsolved problems and how problems were chosen. AGMAI also said it does not support the practice of AI companies testing internal models outsiders cannot use. Whether OpenAI's math gains are accepted is likely to depend less on the count of papers than on outside mathematicians reproducing and validating them, and OpenAI says it is working toward a responsible public release of the model.