FrontierMath Erd\H{o}s

A new benchmark called FrontierMath Erdős (FME), introduced in a paper submitted to arXiv on 6 September 2026, evaluates AI systems on 68 Erdős problems that remained open as of August 2026, requiring them to prove or disprove each conjecture in the Lean proof assistant. The 68 problems were selected by the paper's second author from 652 open problems on erdosproblems.com, and five AI models were tested autonomously under a budget of $300 per problem. GPT-6 Astra scored 3%, the only model to resolve any problem, while all other models scored 0%.

Computer Science Computation and Language Submitted on 6 Sep 2026 Title:FrontierMath Erdős View PDF https://arxiv.org/pdf/2609.25050 HTML experimental https://arxiv.org/html/2609.25050v1 Abstract:We introduce FrontierMath Erdős FME , a benchmark of 68 Erdős problems that are open as of August 2026. To solve a task in FME, AI systems must resolve prove or disprove one of the 68 conjectures in the proof assistant Lean. Our 68 problems were selected by the second author among 652 open problems on this http URL http://erdosproblems.com for their mathematical interest and difficulty. AIs have recently resolved several open problems in mathematics, but these demonstrations fall short of a systematic study of AI capabilities. FME evaluates every AI model on the same fixed problems, autonomously and under the same budget. We evaluated five AIs with a budget of \$300 per problem. One GPT-6 Astra scored 3%, and all others scored 0%. References & Citations Loading... Bibliographic and Citation Tools Bibliographic Explorer What is the Explorer? https://info.arxiv.org/labs/showcase.html arxiv-bibliographic-explorer Connected Papers What is Connected Papers? https://www.connectedpapers.com/about Litmaps What is Litmaps? https://www.litmaps.co/ scite Smart Citations What are Smart Citations? https://www.scite.ai/ Code, Data and Media Associated with this Article alphaXiv What is alphaXiv? https://alphaxiv.org/ CatalyzeX Code Finder for Papers What is CatalyzeX? https://www.catalyzex.com DagsHub What is DagsHub? https://dagshub.com/ Gotit.pub What is GotitPub? http://gotit.pub/faq Hugging Face What is Huggingface? https://huggingface.co/huggingface ScienceCast What is ScienceCast? https://sciencecast.org/welcome Demos Recommenders and Search Tools Influence Flower What are Influence Flowers? https://influencemap.cmlab.dev/ CORE Recommender What is CORE? https://core.ac.uk/services/recommender arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs https://info.arxiv.org/labs/index.html .