Knowledge · OpenAI

GPT-4.1 Max on MMLU-Pro: score, rank and what it means

GPT-4.1 Max scores 87.4 on MMLU-Pro, placing it #26 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
87.4
0–100 scale
Rank
#26
of 600
Percentile
96th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
4.2
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with GPT-4.1 Max 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, GPT-4.1 Max sits at #26 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 4.2 points. The median model in this index scores 76.1, which puts GPT-4.1 Max above the midpoint.

OpenAI models average 84.4 on this benchmark. GPT-4.1 Max is 3.0 points above that provider line, so it is a stronger result than the average OpenAI model.

Among frontier models, the average is 86.9. GPT-4.1 Max is 0.5 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 87.4 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 $17.34 per million input tokens, GPT-4.1 Max 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
o3 Reasoning OpenAI 200000 $18.07 85.3
o4 Pro OpenAI 1000000 $19.37 87.3
Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
GPT-5.2 Max OpenAI 1000000 $21.39 89.2
GPT-4.1 Max OpenAI 400000 $17.34 84.7
GPT-4.1 Reasoning OpenAI 1000000 $16.97 83.8
GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4

Other benchmarks for GPT-4.1 Max

BenchmarkScoreRankPercentileRelative
GPQA Diamond 81.2 42 93th
SWE-bench Verified 74.8 42 93th
HumanEval 88.8 59 90th
MATH-500 87.3 73 88th
AIME 2025 84.9 40 93th
LiveCodeBench 78.5 59 90th
IFEval 92.1 37 94th
TruthfulQA 85.4 61 90th
HellaSwag 90.7 69 89th
MMMU 80.5 51 92th
Arena Elo 1467.6 39 94th

FAQ

What score does GPT-4.1 Max get on MMLU-Pro?

GPT-4.1 Max scores 87.4 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does GPT-4.1 Max rank on MMLU-Pro?

It ranks #26 of 600 models, in the 96th percentile. The leader is GPT-5.2 Pro at 91.6.

Is GPT-4.1 Max 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 GPT-4.1 Max cost?

GPT-4.1 Max costs $17.34 per million input tokens and $66.38 per million output tokens.

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