
Anthropic used Claude to formalize Wiles's proof of Fermat's Last Theorem into 13 million lines of Lean code.
The task took 11 days, far less than the years mathematicians expected.
The milestone builds on prior AI math advances by Anthropic and rivals.
What happened
Anthropic PBC used its Claude AI to create a computer-verifiable version of Andrew Wiles's 1995 proof of Fermat's Last Theorem. The formalized proof consists of 13 million lines of Lean code, making it the largest file of its kind ever.
Why it matters
Formalizing a proof rules out human error and helps mathematicians share information. The task, expected to take years, was completed in 11 days using an internal research model that is roughly on par with Claude Fable 5.1.
What to watch
The model generated 6 billion tokens of output and proved 29,500 intermediate theorems. Claude succeeded only after gaining access to an open-source tool called Prove2Me, which helps AI agents decide the next step and lowers inference costs.
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The formalization of Wiles's proof is a notable step in using AI for mathematics. Wiles's original proof spanned 129 pages and took months to verify manually. Formalization is notoriously difficult because proofs often omit explanations that computers need, and a single error can invalidate later code. Anthropic's model overcame these challenges by generating 6 billion tokens over 11 days, a task that mathematicians had estimated would take years. The use of Prove2Me appears to have been pivotal, turning an unsuccessful attempt into a breakthrough.
This work follows another Anthropic achievement announced a month earlier, where Claude was used to discover new information about the Riemann zeta function. Rival OpenAI also applied its latest Astra model to solve several Erdos problems last month. Together, these advances suggest a growing trend of using large language models to tackle complex mathematical proofs, though the article does not claim this is a universal solution. The comments from mathematician Kevin Buzzard, whose work was used, indicate that AI formalization artifacts are now robust enough to build upon, lending credibility to the milestone.
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