@rohanpaul_ai: $2K of tokens costs less than sending 2 people to a conference, and that gap is what changes the calculation for open p…
Summary
OpenAI reports that an internal version of its next major model (Astra) solved 10 long-standing open problems in math and theoretical computer science for roughly $2,000 in tokens, with formal Lean certificates.
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Cached at: 08/03/26, 09:52 PM
$2K of tokens costs less than sending 2 people to a conference, and that gap is what changes the calculation for open problems.
An internal version of Astra, OpenAI’s next major model, resolved 10 long-standing open problems in math and theoretical computer science for about $2K in tokens.
complete with formal Lean certificates.
OpenAI (@OpenAI): An internal version of our next major model produced 10 new results on long-standing open problems in mathematics and theoretical computer science, using roughly $2,000 worth of tokens at GPT-5.6 Sol API rates.
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@OpenAI: An internal version of our next major model produced 10 new results on long-standing open problems in mathematics and t…
OpenAI's internal next major model produced 10 new results on long-standing open problems in mathematics and theoretical computer science, using roughly $2,000 worth of tokens at GPT-5.6 Sol API rates.
The inference cost for Astra to solve 10 long-open math problems was roughly $2,000. Lean proofs are on GitHub.
Astra, an unreleased AI system, produced machine-checkable Lean 4 proofs for 10 long-open math problems at roughly $2,000 inference cost, sparking debate about the true cost and significance of AI-discovered mathematics.
Ten advances in mathematics and theoretical computer science
OpenAI used an internal model, Astra, to solve ten mathematical problems that had stalled for over a decade, spending under $2,000 per problem and releasing Lean 4 formalizations and a paper. The results prompt reflections on AI's role in mathematics.