Humanity's Last Exam
Authors:
Long Phan,
Alice Gatti,
Ziwen Han,
Nathaniel Li,
Josephina Hu,
Hugh Zhang,
Chen Bo Calvin Zhang,
Mohamed Shaaban,
John Ling,
Sean Shi,
Michael Choi,
Anish Agrawal,
Arnav Chopra,
Adam Khoja,
Ryan Kim,
Richard Ren,
Jason Hausenloy,
Oliver Zhang,
Mantas Mazeika,
Dmitry Dodonov,
Tung Nguyen,
Jaeho Lee,
Daron Anderson,
Mikhail Doroshenko,
Alun Cennyth Stokes
, et al. (1133 additional authors not shown)
Abstract:
Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90\% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of…
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Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in difficulty: LLMs now achieve over 90\% accuracy on popular benchmarks like MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In response, we introduce Humanity's Last Exam (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage. HLE consists of 2,500 questions across dozens of subjects, including mathematics, humanities, and the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading. Each question has a known solution that is unambiguous and easily verifiable, but cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between current LLM capabilities and the expert human frontier on closed-ended academic questions. To inform research and policymaking upon a clear understanding of model capabilities, we publicly release HLE at https://lastexam.ai.
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Submitted 28 July, 2026; v1 submitted 24 January, 2025;
originally announced January 2025.