Knowledge · Google DeepMind

Gemini 2.5 Pro Mini on MMLU-Pro: score, rank and what it means

Gemini 2.5 Pro Mini scores 79.1 on MMLU-Pro, placing it #206 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
79.1
0–100 scale
Rank
#206
of 600
Percentile
66th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
12.5
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Gemini 2.5 Pro 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, Gemini 2.5 Pro Mini sits at #206 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 12.5 points. The median model in this index scores 76.1, which puts Gemini 2.5 Pro Mini above the midpoint.

Google DeepMind models average 80.4 on this benchmark. Gemini 2.5 Pro Mini is 1.3 points below that provider line, so it is a weaker result than the average Google DeepMind model.

Among multimodal models, the average is 80.0. Gemini 2.5 Pro Mini is 0.9 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 79.1 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 $10.07 per million input tokens, Gemini 2.5 Pro 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
Sonar Pro Pro Perplexity 200000 $13.59 79.7
Codestral Mistral AI 65536 $4.19 77.6
Llama 4 Scout Chat Meta AI 32768 $4.66 78.0
GPT-5.1 Mini OpenAI 128000 $12.19 77.7
Gemini 2.5 Pro Mini Google DeepMind 128000 $10.07 74.2
Sonar Perplexity 200000 $10.57 76.0
ERNIE 4.0 Baidu 32768 $11.37 76.7

Other benchmarks for Gemini 2.5 Pro Mini

BenchmarkScoreRankPercentileRelative
GPQA Diamond 69.9 266 56th
SWE-bench Verified 63.6 242 60th
HumanEval 79.0 265 56th
MATH-500 76.0 298 50th
AIME 2025 68.2 292 51th
LiveCodeBench 65.4 284 53th
IFEval 81.5 287 52th
TruthfulQA 78.4 239 60th
HellaSwag 83.3 312 48th
MMMU 71.4 263 56th
Arena Elo 1399.4 209 65th

FAQ

What score does Gemini 2.5 Pro Mini get on MMLU-Pro?

Gemini 2.5 Pro Mini scores 79.1 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Gemini 2.5 Pro Mini rank on MMLU-Pro?

It ranks #206 of 600 models, in the 66th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Gemini 2.5 Pro 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 Gemini 2.5 Pro Mini cost?

Gemini 2.5 Pro Mini costs $10.07 per million input tokens and $53.47 per million output tokens.

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