Knowledge · OpenAI

GPT-5.1 Nano on MMLU-Pro: score, rank and what it means

GPT-5.1 Nano scores 77.0 on MMLU-Pro, placing it #278 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
77.0
0–100 scale
Rank
#278
of 600
Percentile
54th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
14.6
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with GPT-5.1 Nano 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-5.1 Nano sits at #278 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 14.6 points. The median model in this index scores 76.1, which puts GPT-5.1 Nano above the midpoint.

OpenAI models average 84.4 on this benchmark. GPT-5.1 Nano is 7.4 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-5.1 Nano is 3.0 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 77.0 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 $9.56 per million input tokens, GPT-5.1 Nano 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
Yi-Large 01.AI 32768 $3.40 73.5
Claude Haiku 4.5 Mini Anthropic 16384 $8.76 71.6
DBRX Databricks 65536 $3.29 73.3
Doubao 1.5 Pro Mini ByteDance 32768 $8.30 72.3
GPT-5.1 Nano OpenAI 32768 $9.56 74.1
Mixtral Instruct Mistral AI 65536 $3.35 72.9
Llama 3 Anyscale Instruct Anyscale 200000 $3.91 75.7

Other benchmarks for GPT-5.1 Nano

BenchmarkScoreRankPercentileRelative
GPQA Diamond 71.2 235 61th
SWE-bench Verified 63.1 251 58th
HumanEval 76.1 328 45th
MATH-500 79.5 220 63th
AIME 2025 66.1 328 45th
LiveCodeBench 63.9 323 46th
IFEval 82.6 257 57th
TruthfulQA 78.1 253 58th
HellaSwag 85.5 227 62th
MMMU 72.0 243 60th
Arena Elo 1378.2 280 53th

FAQ

What score does GPT-5.1 Nano get on MMLU-Pro?

GPT-5.1 Nano scores 77.0 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does GPT-5.1 Nano rank on MMLU-Pro?

It ranks #278 of 600 models, in the 54th percentile. The leader is GPT-5.2 Pro at 91.6.

Is GPT-5.1 Nano 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-5.1 Nano cost?

GPT-5.1 Nano costs $9.56 per million input tokens and $43.06 per million output tokens.

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