OpenAI Says a Secret AI Model Cracked Hundreds of Open Math Problems in One Prompt—Mathematicians Want Receipts
OpenAI published 722 math manuscripts on GitHub from an unreleased internal model. Only 162 of the 722 papers have a formalized main result, and some unformalized results could have issues.
Intelligence analysis by Qwen 2.5 (3B)

OpenAI released 722 math papers from an unreleased model, sparking debate among mathematicians who want more details and transparency.
OpenAI made a secret AI model solve math problems. Only a few of the problems were checked by other people. Mathematicians want to see more details about how the model worked.
Analysis
{"heading_1":"The Release of 722 Math Papers","subheading_1":"OpenAI's Unreleased Model","content_1":"OpenAI published 722 math manuscripts on GitHub from an unreleased internal model. The company claims that almost everything came from a single prompt handed to a single AI agent.","heading_2":"Formalization and Transparency","subheading_2":"Only 162 of the 722 papers have a formalized main result, and some unformalized results could have issues.","content_2":"OpenAI itself says not all manuscripts have Lean formalizations and that 'some of the unformalized results could have issues.' The Institute for Advanced Study recommends that OpenAI release the model name, the prompts, a summarized chain of thought, the time taken and the compute cost for every result.","heading_3":"Mathematicians' Concerns","subheading_3":"Andrew Sutherland and others are skeptical of the claims and want more details.","content_3":"Andrew Sutherland, a mathematician at MIT, says the one-prompt, single-agent claim is unverified until the model is released. He wants receipts and more transparency from OpenAI."}
Key points
- OpenAI released 722 math papers from an unreleased model
- Only 162 of the 722 papers have a formalized main result
- Mathematicians want more transparency and details about the model
The model could lead to new mathematical discoveries and help solve problems that were previously unsolvable.
The results could be wrong or not verified, and mathematicians want more information before they can trust the model's claims.


