legal benchmark
MMLU (Massive Multitask Language Understanding) is a comprehensive benchmark that measures a text model's multitask accuracy across 57 diverse academic and professional subjects. The test covers elementary mathematics, US history, computer science, law, morality, business ethics, clinical knowledge, and many other domains spanning STEM, humanities, social sciences, and professional fields. To attain high accuracy, models must possess extensive world knowledge and problem-solving ability.
Updated Aug 11, 2026
Higher score ranks better on this benchmark.
| 01 | GO | 35.6% | 100.0% | 2 | C | |
| 02 | GO | 22.3% | 0.0% | 2 | C |
A closer view of the leading scores on this benchmark.
The leading models and scores on this benchmark.
What OpenAI MMLU measures and how its scores work.
MMLU (Massive Multitask Language Understanding) is a comprehensive benchmark that measures a text model's multitask accuracy across 57 diverse academic and professional subjects. The test covers elementary mathematics, US history, computer science, law, morality, business ethics, clinical knowledge, and many other domains spanning STEM, humanities, social sciences, and professional fields. To attain high accuracy, models must possess extensive world knowledge and problem-solving ability.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about OpenAI MMLU.
Gemma 3n E4B Instructed is currently ranked first with 35.6%.
MMLU (Massive Multitask Language Understanding) is a comprehensive benchmark that measures a text model's multitask accuracy across 57 diverse academic and professional subjects. The test covers elementary mathematics, US history, computer science, law, morality, business ethics, clinical knowledge, and many other domains spanning STEM, humanities, social sciences, and professional fields. To attain high accuracy, models must possess extensive world knowledge and problem-solving ability.
Yes. Higher values rank better for this benchmark.
2 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.