Multimodal · Google DeepMind

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

Gemini 3 Pro Reasoning scores 80.8 on MMMU, placing it #46 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
80.8
0–100 scale
Rank
#46
of 600
Percentile
92th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
6.1
points

Score distribution

The chart shows the top 10 models on MMMU, with Gemini 3 Pro Reasoning 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 Reasoning sits at #46 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 6.1 points. The median model in this index scores 70.0, which puts Gemini 3 Pro Reasoning above the midpoint.

Google DeepMind models average 74.9 on this benchmark. Gemini 3 Pro Reasoning is 5.9 points above that provider line, so it is a stronger result than the average Google DeepMind model.

Among frontier models, the average is 81.6. Gemini 3 Pro Reasoning is 0.8 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 80.8 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 $19.69 per million input tokens, Gemini 3 Pro Reasoning 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
Claude Sonnet 4.5 Turbo Anthropic 1000000 $18.37 85.9
Gemini 3 Flash Max Google DeepMind 1000000 $17.43 85.0
Claude Sonnet 4.5 Anthropic 400000 $17.84 86.0
o4 OpenAI 2000000 $17.74 85.4
Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
Grok 4 Reasoning xAI 2000000 $19.67 87.8
o3 Max OpenAI 2000000 $17.82 84.8

Other benchmarks for Gemini 3 Pro Reasoning

BenchmarkScoreRankPercentileRelative
MMLU-Pro 90.1 5 99th
GPQA Diamond 83.9 13 98th
SWE-bench Verified 76.3 27 96th
HumanEval 90.2 43 93th
MATH-500 93.3 9 99th
AIME 2025 88.8 12 98th
LiveCodeBench 82.0 25 96th
IFEval 93.8 13 98th
TruthfulQA 90.3 2 100th
HellaSwag 93.5 18 97th
Arena Elo 1485.0 16 97th

FAQ

What score does Gemini 3 Pro Reasoning get on MMMU?

Gemini 3 Pro Reasoning scores 80.8 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does Gemini 3 Pro Reasoning rank on MMMU?

It ranks #46 of 600 models, in the 92nd percentile. The leader is GPT-5.2 Max at 86.9.

Is Gemini 3 Pro Reasoning 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 Reasoning cost?

Gemini 3 Pro Reasoning costs $19.69 per million input tokens and $98.36 per million output tokens.

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