legal benchmark
OpenAI MMLU measures a text model's multitask accuracy across 57 academic and professional subjects.
Updated Sep 5, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelGO | Score35.60% | Percentile100.00% | Participants2 | EvidenceC | Evaluated |
| Rank02 | ModelGO | Score22.30% | Percentile0.00% | Participants2 | EvidenceC | Evaluated |
The leading models and scores on this benchmark.
A closer view of the leading scores on this benchmark.
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
What OpenAI MMLU measures and how its scores work.
MMLU (Massive Multitask Language Understanding) is a benchmark covering 57 subjects across STEM, humanities, social sciences, and professional fields.
It measures multitask accuracy in areas including elementary mathematics, US history, computer science, law, morality, business ethics, and clinical knowledge, with the metric reported as Score in ratio units.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
LLM Stats. 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 35.60%.
The current leaders are Gemma 3n E4B Instructed (35.60%) and Gemma 3n E2B Instructed (22.30%).
No matched official input price is currently available.
No matched runtime record is currently available.
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
It measures multitask accuracy in areas including elementary mathematics, US history, computer science, law, morality, business ethics, and clinical knowledge, with the metric reported as Score in ratio units.
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.
Ranking basisThis openai mmlu AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
Selection summary
Gemma 3n E4B Instructed currently leads OpenAI MMLU with 35.60%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price, and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.