legal benchmark
MMLU-Base Leaderboard
Base version of the Massive Multitask Language Understanding benchmark, evaluating language models across 57 tasks including elementary mathematics, US history, computer science, law, and other professional and academic subjects. Designed to comprehensively measure the breadth and depth of a model's academic and professional understanding.
Updated Aug 17, 2026
Models1
Model coverage1
MetricScore
EvidenceB
MMLU-Base Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelAC | Score68.0% | Percentile100.0% | Participants1 | EvidenceC | Evaluated |
MMLU-Base Highlights
The leading models and scores on this benchmark.
The Top AI Models for MMLU-Base
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis mmlu-base AI model leaderboard uses descending score in the benchmark's original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
- 01ACQwen2.5-Coder 7B InstructAlibaba Cloud / Qwen Team
- Score
- 68.0%
- Price
- $0.14 input / $0.29 output per 1M tokens
Strengths
- Ranks #1 of 1 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures MMLU-Base, not total model capability
Selection summary
Best AI Models for MMLU-Base
Qwen2.5-Coder 7B Instruct currently leads MMLU-Base with 68.0%. 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.
What is MMLU-Base?
What MMLU-Base measures and how its scores work.
Base version of the Massive Multitask Language Understanding benchmark, evaluating language models across 57 tasks including elementary mathematics, US history, computer science, law, and other professional and academic subjects. Designed to comprehensively measure the breadth and depth of a model's academic and professional understanding.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- MMLU-Base
- Modality
- text
- Primary category
- legal
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- mmlu-base|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about MMLU-Base.
Which model scores highest on MMLU-Base?
Qwen2.5-Coder 7B Instruct is currently ranked first with 68.0%.
What does MMLU-Base measure?
Base version of the Massive Multitask Language Understanding benchmark, evaluating language models across 57 tasks including elementary mathematics, US history, computer science, law, and other professional and academic subjects. Designed to comprehensively measure the breadth and depth of a model's academic and professional understanding.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
1 model results are currently shown.
Does this benchmark affect the overall score?
No. This benchmark is shown for reference but does not contribute to the overall score.