MMLU-STEM
STEM-focused subset of the Massive Multitask Language Understanding benchmark, evaluating language models on science, technology, engineering, and mathematics topics including physics, chemistry, mathematics, and other technical subjects.
Qwen2.5 32B Instruct from Alibaba Cloud / Qwen Team currently leads the MMLU-STEM leaderboard with a score of 0.809 across 2 evaluated AI models.
What MMLU-STEM measures
MMLU-STEM is a text benchmark that evaluates large language models on math, physics, reasoning, and chemistry tasks. LLM Stats tracks 2 models on this benchmark, with a maximum possible score of 1. Current average across reported models is 0.8, with the leader reaching 0.8.
Compare leaders on the best AI for math, best AI for physics, best AI for reasoning and best AI for chemistry leaderboards.
Publication
- Paper
- Measuring Massive Multitask Language Understanding
- Authors
- Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, and 3 others
- Published
- arXiv
- 2009.03300
Abstract
We propose a new test to measure a text model's multitask accuracy. The test covers 57 tasks including elementary mathematics, US history, computer science, law, and more. To attain high accuracy on this test, models must possess extensive world knowledge and problem solving ability. We find that while most recent models have near random-chance accuracy, the very largest GPT-3 model improves over random chance by almost 20 percentage points on average. However, on every one of the 57 tasks, the best models still need substantial improvements before they can reach expert-level accuracy. Models also have lopsided performance and frequently do not know when they are wrong. Worse, they still have near-random accuracy on some socially important subjects such as morality and law. By comprehensively evaluating the breadth and depth of a model's academic and professional understanding, our test can be used to analyze models across many tasks and to identify important shortcomings.
Qwen2.5 32B Instruct leads with 80.9%, followed by Qwen2.5 14B Instruct at 76.4%.
Progress Over Time
Interactive timeline showing model performance evolution on MMLU-STEM
MMLU-STEM Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 |  Alibaba Cloud / Qwen Team | 33B | — | — | ||
| 2 | Alibaba Cloud / Qwen Team | 15B | — | — |
FAQ
Common questions about MMLU-STEM.
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