Multimodal · Google DeepMind

Gemini 3 Pro Mini on MMMU: score, rank and what it means

Gemini 3 Pro Mini scores 74.5 on MMMU, placing it #169 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
74.5
0–100 scale
Rank
#169
of 600
Percentile
72th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
12.4
points

Score distribution

The chart shows the top 10 models on MMMU, with Gemini 3 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 3 Pro Mini sits at #169 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 12.4 points. The median model in this index scores 70.0, which puts Gemini 3 Pro Mini above the midpoint.

Google DeepMind models average 74.9 on this benchmark. Gemini 3 Pro Mini is 0.4 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 3 Pro Mini is 0.2 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 74.5 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 $12.27 per million input tokens, Gemini 3 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
Hunyuan-Turbo Reasoning Tencent 128000 $11.89 77.5
Command A Max Cohere 400000 $14.28 79.9
ERNIE 4.0 Pro Baidu 200000 $12.58 77.5
Grok 4 Mini xAI 65536 $12.21 77.9
Gemini 3 Pro Mini Google DeepMind 128000 $12.27 78.1
Seed-OSS Instruct ByteDance 128000 $3.79 76.0
ERNIE 4.5 Reasoning Baidu 1000000 $14.36 79.8

Other benchmarks for Gemini 3 Pro Mini

BenchmarkScoreRankPercentileRelative
MMLU-Pro 79.4 199 67th
GPQA Diamond 72.1 217 64th
SWE-bench Verified 68.0 146 76th
HumanEval 83.5 143 76th
MATH-500 81.3 182 70th
AIME 2025 77.5 121 80th
LiveCodeBench 70.8 175 71th
IFEval 86.2 149 75th
TruthfulQA 80.0 177 71th
HellaSwag 85.8 222 63th
Arena Elo 1419.9 149 75th

FAQ

What score does Gemini 3 Pro Mini get on MMMU?

Gemini 3 Pro Mini scores 74.5 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Gemini 3 Pro Mini rank on MMMU?

It ranks #169 of 600 models, in the 72nd percentile. The leader is GPT-5.2 Max at 86.9.

Is Gemini 3 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 3 Pro Mini cost?

Gemini 3 Pro Mini costs $12.27 per million input tokens and $57.81 per million output tokens.

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