Multimodal · Google DeepMind

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

Gemini 2.5 Pro Mini scores 71.4 on MMMU, placing it #263 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
71.4
0–100 scale
Rank
#263
of 600
Percentile
56th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
15.5
points

Score distribution

The chart shows the top 10 models on MMMU, with Gemini 2.5 Pro Mini 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, Gemini 2.5 Pro Mini sits at #263 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 15.5 points. The median model in this index scores 70.0, which puts Gemini 2.5 Pro Mini above the midpoint.

Google DeepMind models average 74.9 on this benchmark. Gemini 2.5 Pro Mini is 3.5 points below that provider line, so it is a weaker result than the average Google DeepMind model.

Among multimodal models, the average is 74.3. Gemini 2.5 Pro Mini is 2.9 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 71.4 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 $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 MMMU. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Sonar Pro Perplexity 65536 $11.25 77.1
Sonar Reasoning Perplexity 200000 $11.48 76.2
Firefunction Max Fireworks AI 32768 $9.12 73.2
Fusion Pro OpenRouter 65536 $8.69 72.2
Gemini 2.5 Pro Mini Google DeepMind 128000 $10.07 74.2
Llama 3.1 Cerebras Instruct Cerebras 65536 $4.11 76.1
Llama 3.1 Turbo Instruct Together AI 32768 $4.21 76.7

Other benchmarks for Gemini 2.5 Pro Mini

BenchmarkScoreRankPercentileRelative
MMLU-Pro 79.1 206 66th
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
Arena Elo 1399.4 209 65th

FAQ

What score does Gemini 2.5 Pro Mini get on MMMU?

Gemini 2.5 Pro Mini scores 71.4 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Gemini 2.5 Pro Mini rank on MMMU?

It ranks #263 of 600 models, in the 56th percentile. The leader is GPT-5.2 Max at 86.9.

Is Gemini 2.5 Pro Mini 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 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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