Knowledge Benchmark

MMLU-Pro

MMLU-Pro - extended MMLU covering 14 categories with complex reasoning questions.

Category

Knowledge

Score type

percent

Scale

100%

higher is better

Models tested

36

What is MMLU-Pro?

MMLU-Pro is the harder successor of MMLU: 14 subject areas, ten answer options instead of four and questions that require real reasoning instead of simply recognising trivia. This reduces random-guess luck and separates strong models more clearly.

What does it test?

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

  • knowledge combined with multi-step reasoning
  • robustness against guessing (10 instead of 4 options)
  • harder, more discriminative questions
  • broad coverage of 14 academic areas

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.

Frequently asked questions

What is the MMLU-Pro benchmark?

MMLU-Pro is the harder successor of MMLU: 14 subject areas, ten answer options instead of four and questions that require real reasoning instead of simply recognising trivia. This reduces random-guess luck and separates strong models more clearly.

What does MMLU-Pro test?

MMLU-Pro mainly measures broad factual and academic knowledge. Concretely, it checks: knowledge combined with multi-step reasoning; robustness against guessing (10 instead of 4 options); harder, more discriminative questions.

How is the MMLU-Pro 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 data and scores?

The official source is https://huggingface.co/datasets/TIGER-Lab/MMLU-Pro. 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/scores) or pull it directly from the Open LLM Radar API with any HTTP client.

Model scores 36 models tested

Reset
# Model Score Date Source Verified
1 Kimi K2.6
Moonshot AI
88.1%
04.06.2026 Report Unverified
2 Muse-Spark-Open-816B-A42B
Meta Superintelligence Lab
87.9%
— Report Unverified
3 DeepSeek-V4-Pro
DeepSeek
87.5%
04.06.2026 Report Unverified
4 NVIDIA-Nemotron-3-Ultra-550B-A55B-BF16
NVIDIA
86.8%
04.06.2026 Report Verified
5 Qwen3.5-122B-A10B
Qwen Team (Alibaba Cloud)
86.7%
01.02.2026 Report Verified
6 Qwen3.6-27B
Qwen Team (Alibaba Cloud)
86.2%
22.04.2026 Qwen Team (official model card) Verified
7 DeepSeek-V4-Flash
DeepSeek
86.2%
26.06.2026 Report Verified
8 Qwen3.5-27B
Qwen Team (Alibaba Cloud)
86.1%
16.04.2026 Qwen Team (official model card - comparison) Unverified
9 Qwen3.8-27B
Qwen Team (Alibaba Cloud)
85.7%
21.10.2026 Report Unverified
10 Qwen3.5-35B-A3B
Qwen Team (Alibaba Cloud)
85.3%
16.04.2026 Qwen Team (official model card - comparison) Unverified
11 Qwen3.6-35B-A3B
Qwen Team (Alibaba Cloud)
85.2%
16.04.2026 Qwen Team (official model card); KRAFTON re-eval (Raon-1-mini-preview card, gpt-5.6-luna harness): 85.9 Verified
12 Gemma4-31B-it
Google
85.2%
16.04.2026 Qwen Team (official model card - comparison) Unverified
13 Qwen3-235B-A22B
Qwen Team (Alibaba Cloud)
84.4%
01.02.2026 Report Unverified
14 Ripple-65B Preview
Ricursive Intelligence
84.2%
— Report Verified
15 Muse-Glimmer-30B
Meta Superintelligence Lab
84%
21.10.2026 Report Unverified
16 Qwen3-Next-80B-A3B-Thinking
Qwen
82.7%
10.09.2025 Report Verified
17 Gemma4-26B-A4B
Google
82.6%
16.04.2026 Qwen Team (official model card - comparison); KRAFTON re-eval (Raon-1-mini-preview card, gpt-5.6-luna harness): 82.9 Unverified
18 Qwen3-30B-A3B-Thinking-2507
Qwen
80.9%
31.07.2025 Report Verified
19 Qwen3.5-4B
Qwen
79.1%
01.02.2026 Report Verified
20 Qwen3-30B-A3B
Qwen
78.5%
29.04.2025 Report Verified
21 ERNIE-5.5-Flash-Base
Baidu
78.4%
— HF model card baidu/ERNIE-5.5-Flash-Base (EM, 5-shot, Unified Pipeline) Unverified
22 Qwen3-VL-30B-A3B
Qwen
77.8%
04.10.2025 Report Verified
23 Gemma4-12B
Google
77.2%
02.07.2026 Report Verified
24 Raon-1 mini
KRAFTON AI
76.5%
21.10.2026 Report Verified
25 DeepSeek-V4-Pro
DeepSeek
73.5%
26.06.2026 Report Verified
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What now?

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