legal benchmark
MMLU (CoT) Leaderboard
Chain-of-Thought variant 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. This version uses chain-of-thought prompting to elicit step-by-step reasoning.
Updated Aug 17, 2026
Models3
Model coverage3
MetricScore
EvidenceB
MMLU (CoT) Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelME | Score88.6% | Percentile100.0% | Participants3 | EvidenceC | Evaluated |
| Rank02 | ModelME | Score86.0% | Percentile50.0% | Participants3 | EvidenceC | Evaluated |
| Rank03 | ModelME | Score73.0% | Percentile0.0% | Participants3 | EvidenceC | Evaluated |
MMLU (CoT) Highlights
The leading models and scores on this benchmark.
MMLU (CoT) Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for MMLU (CoT)
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis mmlu (cot) 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.
- 01ME
- Score
- 88.6%
- Speed
- Up to 100 tok/s via Bedrock
Strengths
- Ranks #1 of 3 compared models
- 100th percentile on this benchmark
- C evidence result
Considerations
- This result measures MMLU (CoT), not total model capability
- 02ME
- Score
- 86.0%
- Speed
- Up to 1,204 tok/s via Cerebras
Strengths
- Ranks #2 of 3 compared models
- 50th percentile on this benchmark
- C evidence result
Considerations
- This result measures MMLU (CoT), not total model capability
- 03ME
- Score
- 73.0%
- Speed
- Up to 2,047 tok/s via Cerebras
Strengths
- Ranks #3 of 3 compared models
- 0th percentile on this benchmark
- C evidence result
Considerations
- This result measures MMLU (CoT), not total model capability
Selection summary
Best AI Models for MMLU (CoT)
Llama 3.1 405B Instruct currently leads MMLU (CoT) with 88.6%. 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 (CoT)?
What MMLU (CoT) measures and how its scores work.
Chain-of-Thought variant 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. This version uses chain-of-thought prompting to elicit step-by-step reasoning.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- MMLU (CoT)
- Modality
- text
- Primary category
- legal
- Score direction
- higher
- LLMBoard eligible
- Yes
- Evaluation key
- mmlu-(cot)|llm-stats-current
Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about MMLU (CoT).
Which model scores highest on MMLU (CoT)?
Llama 3.1 405B Instruct is currently ranked first with 88.6%.
What does MMLU (CoT) measure?
Chain-of-Thought variant 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. This version uses chain-of-thought prompting to elicit step-by-step reasoning.
Is a higher score better?
Yes. Higher values rank better for this benchmark.
How many models are compared?
3 model results are currently shown.
Does this benchmark affect the overall score?
Yes. This benchmark can contribute to the current LLMBoard capability score.