Knowledge · Anthropic

Claude 3.7 Sonnet Reasoning on MMLU-Pro: score, rank and what it means

Claude 3.7 Sonnet Reasoning scores 86.4 on MMLU-Pro, placing it #45 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
86.4
0–100 scale
Rank
#45
of 600
Percentile
93th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
5.2
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Claude 3.7 Sonnet Reasoning highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, Claude 3.7 Sonnet Reasoning sits at #45 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 5.2 points. The median model in this index scores 76.1, which puts Claude 3.7 Sonnet Reasoning above the midpoint.

Anthropic models average 83.4 on this benchmark. Claude 3.7 Sonnet Reasoning is 3.0 points above that provider line, so it is a stronger result than the average Anthropic model.

Among frontier models, the average is 86.9. Claude 3.7 Sonnet Reasoning is 0.5 points below that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 86.4 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.

Price context

At $16.30 per million input tokens, Claude 3.7 Sonnet Reasoning is above the median input price of $4.00 across the 600 models scored on MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Qwen3-Max Turbo Alibaba Cloud 1000000 $17.70 84.7
Gemini 2.5 Pro Max Google DeepMind 200000 $16.94 84.8
Claude Haiku 4.5 Max Anthropic 200000 $15.98 83.8
Kimi K2 Instruct Moonshot AI 1000000 $5.80 82.3
Claude 3.7 Sonnet Reasoning Anthropic 128000 $16.30 83.7
Claude Sonnet 4.5 Pro Anthropic 1000000 $18.73 86.7
o4 Max OpenAI 2000000 $19.51 86.2

Other benchmarks for Claude 3.7 Sonnet Reasoning

BenchmarkScoreRankPercentileRelative
GPQA Diamond 81.3 39 94th
SWE-bench Verified 71.0 95 84th
HumanEval 89.2 57 91th
MATH-500 90.3 45 93th
AIME 2025 79.8 92 85th
LiveCodeBench 79.6 48 92th
IFEval 90.1 69 89th
TruthfulQA 86.2 47 92th
HellaSwag 90.4 75 88th
MMMU 76.5 122 80th
Arena Elo 1464.4 44 93th

FAQ

What score does Claude 3.7 Sonnet Reasoning get on MMLU-Pro?

Claude 3.7 Sonnet Reasoning scores 86.4 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Claude 3.7 Sonnet Reasoning rank on MMLU-Pro?

It ranks #45 of 600 models, in the 93rd percentile. The leader is GPT-5.2 Pro at 91.6.

Is Claude 3.7 Sonnet Reasoning good at MMLU-Pro?

Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.

How is the MMLU-Pro score calculated?

MMLU-Pro is a knowledge benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.

What does Claude 3.7 Sonnet Reasoning cost?

Claude 3.7 Sonnet Reasoning costs $16.30 per million input tokens and $77.62 per million output tokens.

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