Multimodal · OpenAI

GPT-4.1 on MMMU: score, rank and what it means

GPT-4.1 scores 76.3 on MMMU, placing it #132 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
76.3
0–100 scale
Rank
#132
of 600
Percentile
78th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
10.6
points

Score distribution

The chart shows the top 10 models on MMMU, with GPT-4.1 highlighted. Longer bars mean higher scores.

GPT-5.2 Max 86.9
GPT-5.1 Reasoning 86.2
GPT-5.2 85.3
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.1 Max 85.1
Grok 4 Pro 84.9
Claude Opus 4.5 Reasoning 84.6
Claude Sonnet 4.5 Pro 84.5
GPT-5.2 Pro 84.4
GPT-5.2 Vision 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.2 OpenAI 2000000 $19.71 88.0
4 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
5 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
6 Grok 4 Pro xAI 1000000 $19.00 85.4
7 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
8 Claude Sonnet 4.5 Pro Anthropic 1000000 $18.73 86.7
9 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
10 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4

What this score means

On MMMU, GPT-4.1 sits at #132 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 10.6 points. The median model in this index scores 70.0, which puts GPT-4.1 above the midpoint.

OpenAI models average 79.3 on this benchmark. GPT-4.1 is 3.0 points below that provider line, so it is a weaker result than the average OpenAI model.

Among multimodal models, the average is 74.3. GPT-4.1 is 2.0 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 76.3 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 $15.71 per million input tokens, GPT-4.1 is above the median input price of $4.00 across the 600 models scored on MMMU. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 4 Scout Chat Meta AI 32768 $4.66 78.0
Magistral Instruct Mistral AI 65536 $4.48 78.4
MiniMax-Text Chat MiniMax 128000 $4.26 77.8
Reka Core Pro Reka AI 65536 $13.44 79.9
GPT-4.1 OpenAI 1000000 $15.71 82.4
Kimi K1.5 Base Moonshot AI 65536 $4.34 77.4
Mistral Large 3 Mistral AI 128000 $5.41 81.7

Other benchmarks for GPT-4.1

BenchmarkScoreRankPercentileRelative
MMLU-Pro 86.2 48 92th
GPQA Diamond 76.1 118 80th
SWE-bench Verified 72.2 74 88th
HumanEval 88.3 68 89th
MATH-500 86.8 82 86th
AIME 2025 79.9 89 85th
LiveCodeBench 77.8 66 89th
IFEval 90.4 63 90th
TruthfulQA 81.8 132 78th
HellaSwag 90.3 77 87th
Arena Elo 1432.4 115 81th

FAQ

What score does GPT-4.1 get on MMMU?

GPT-4.1 scores 76.3 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does GPT-4.1 rank on MMMU?

It ranks #132 of 600 models, in the 78th percentile. The leader is GPT-5.2 Max at 86.9.

Is GPT-4.1 good at MMMU?

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 MMMU score calculated?

MMMU is a multimodal 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 cost?

GPT-4.1 costs $15.71 per million input tokens and $64.52 per million output tokens.

Related