Sharing AI progress in mathematics
OpenAI is releasing new mathematical results generated by an internal frontier model, aiming to empower scientists with state-of-the-art capabilities. They consulted with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study to develop best practices for sharing these results. OpenAI plans to responsibly release the model and will continue to evaluate their internal frontier models in mathematics and other sciences to accelerate tool development and advance these fields, acting on community feedback.
Unlike previous AI math research, OpenAI is releasing 722 specific mathematical manuscripts and working towards releasing the model that produced them.
Time & source
Times shown in UTC
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PublishedOffset at this time: UTC+0Oct 6, 2026, 12:00 UTC
IngestedOffset at this time: UTC+0Oct 6, 2026, 23:00 UTC
- Published
- Oct 6, 2026, 12:00
- Ingested
- Oct 6, 2026, 23:00
- Source type
- Official
- Tier
- First-party
- Source status
- Healthy
Tier is a per-source editorial setting, not a per-item score.
Discussion trend
The percentage is based on collected discussion signal, not new comments or independent people. The curve only compares the same topic across time.
- Basis
- Running about 7.3× the median of this source's recent listed items
- Triggering item
- Sharing AI progress in mathematics
- Metric comparison
- 500 vs median 69 (20 baseline samples)
- Detected
- 10/07, 00:00
We’re releasing a broad range of new mathematical results produced by an internal frontier model.
As we look to improve how we share results with the math community, we’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study (opens in a new window) to develop best practices, and we have drawn on their advice and public recommendations (opens in a new window) to inform how we release these results.
For this release, we’re publishing the results in a GitHub repository, with protocols for paper revisions and citations. We’re continuing to explore other community-hosted alternatives for this release which meet the committee’s guidelines. For future releases, we are committed to further improving the quality of the papers via the citations, mathematical exposition, and presentation of the results for better understanding.
As part of our GitHub repository, we are sharing formalizations of many of the proofs in Lean, a programming language that allows mathematical proofs to be checked by a computer. We will update the repository with more formalizations as we obtain them.
To promote scientific transparency and openness, we are also publishing additional details about how we obtained the results in the repository. These include 10 summaries of the model’s reasoning, estimations of compute spent in terms of Pro usage on ChatGPT, and statistics about the number of attempted problems. The average result used the equivalent compute of roughly three hours of ChatGPT Pro thinking.
We want this progress to push the frontier of human knowledge and enable further progress in mathematics. We will be funding a series of workshops, conferences, and special programs around the understanding of major results produced by AI—we will share more on this in the near future.
We want to directly empower scientists with state-of-the-art capabilities and are working to responsibly release the model that produced these results. This is why it is important to continue to evaluate our internal frontier models on mathematics and other sciences, so we can accelerate developing the tools to advance those fields. We will continue to act on feedback from the community and update our standards for future disclosures of major scientific advancements.