Knowledge · OpenAI

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

GPT-4.1 Mini scores 76.7 on MMLU-Pro, placing it #285 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
76.7
0–100 scale
Rank
#285
of 600
Percentile
53th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
14.9
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with GPT-4.1 Mini 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 Mini sits at #285 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 14.9 points. The median model in this index scores 76.1, which puts GPT-4.1 Mini above the midpoint.

OpenAI models average 84.4 on this benchmark. GPT-4.1 Mini is 7.7 points below that provider line, so it is a weaker result than the average OpenAI model.

Among multimodal models, the average is 80.0. GPT-4.1 Mini is 3.3 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 76.7 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 $10.43 per million input tokens, GPT-4.1 Mini 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
Llama 3 DeepInfra Chat DeepInfra 200000 $3.74 75.0
Llama 3 Lambda Chat Lambda 32768 $3.73 74.7
Llama 3 Modal Chat Modal 65536 $3.55 73.3
Sonar Reasoning Perplexity 200000 $11.48 76.2
GPT-4.1 Mini OpenAI 128000 $10.43 74.3
Mistral Small 3 Chat Mistral AI 200000 $3.54 73.7
Auto Pro OpenRouter 8192 $8.41 71.2

Other benchmarks for GPT-4.1 Mini

BenchmarkScoreRankPercentileRelative
GPQA Diamond 69.3 285 53th
SWE-bench Verified 60.9 304 49th
HumanEval 78.9 267 56th
MATH-500 77.9 259 57th
AIME 2025 66.9 314 48th
LiveCodeBench 67.0 249 59th
IFEval 81.4 289 52th
TruthfulQA 79.8 185 69th
HellaSwag 84.9 250 58th
MMMU 73.9 195 68th
Arena Elo 1379.7 274 54th

FAQ

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

GPT-4.1 Mini scores 76.7 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

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

It ranks #285 of 600 models, in the 53rd percentile. The leader is GPT-5.2 Pro at 91.6.

Is GPT-4.1 Mini 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 Mini cost?

GPT-4.1 Mini costs $10.43 per million input tokens and $49.01 per million output tokens.

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