Knowledge Benchmark

MMLU Pro COT

MMLU-Pro with chain-of-thought reasoning. 5-shot.

Category

Knowledge

Score type

percent

Scale

100%

higher is better

Models tested

4

What is MMLU Pro COT?

MMLU Pro COT is a benchmark for broad factual and academic knowledge. The official description says: "MMLU-Pro with chain-of-thought reasoning". Below we describe in simple words what benchmarks of this type generally examine.

What does it test?

MMLU Pro COT measures broad factual and academic knowledge. In detail, it checks:

  • facts and concepts from many academic fields at once
  • harder variants with several plausible answer options
  • knowledge that goes beyond the model's training-set surface forms
  • resisting the plausible-but-wrong answers deliberately included

How to read the score

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better.

Official methodology note: MMLU-Pro with chain-of-thought reasoning. 5-shot.

Frequently asked questions

What is the MMLU Pro COT benchmark?

MMLU Pro COT is a benchmark for broad factual and academic knowledge. The official description says: 'MMLU-Pro with chain-of-thought reasoning'. Below we describe in simple words what benchmarks of this type generally examine.

What does MMLU Pro COT test?

MMLU Pro COT mainly measures broad factual and academic knowledge. Concretely, it checks: facts and concepts from many academic fields at once; harder variants with several plausible answer options; knowledge that goes beyond the model's training-set surface forms.

How is the MMLU Pro COT score calculated?

The score is accuracy: the percentage of tasks answered or solved correctly. 100% means every task was solved perfectly; higher is better. The declared maximum score of this benchmark is 100.0.

Where do I get MMLU Pro COT data and scores?

The official source is https://arxiv.org/abs/2009.03300. The official benchmark page/reference is linked on this page. Every score on Open LLM Radar is also available as open data: download the scores JSON (http://open-llm-radar-api:8000/api/v1/benchmarks/mmlu-pro-cot/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 4 models tested

Reset
# Model Score Date Source Verified
1 Kolibri-1
Aleph Alpha
80%
03.10.2026 Report Verified
2 Gemma 3 27B PT
Google DeepMind
52.2%
27.02.2025 Report Verified
3 Gemma 3 12B PT
Google DeepMind
45.3%
27.02.2025 Report Verified
4 Gemma 3 4B PT
Google DeepMind
29.2%
27.02.2025 Report Verified

What now?

You've seen how models score on MMLU Pro COT — here's what to do next.