Knowledge · Google DeepMind

Gemini 3 Pro Pro on MMLU-Pro: score, rank and what it means

Gemini 3 Pro Pro scores 88.2 on MMLU-Pro, placing it #14 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
88.2
0–100 scale
Rank
#14
of 600
Percentile
98th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
3.4
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Gemini 3 Pro Pro 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 3 Pro Pro sits at #14 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 3.4 points. The median model in this index scores 76.1, which puts Gemini 3 Pro Pro above the midpoint.

Google DeepMind models average 80.4 on this benchmark. Gemini 3 Pro Pro is 7.8 points above that provider line, so it is a stronger result than the average Google DeepMind model.

Among frontier models, the average is 86.9. Gemini 3 Pro Pro is 1.3 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 88.2 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 $19.80 per million input tokens, Gemini 3 Pro Pro 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
Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9
Qwen3-Max Pro Alibaba Cloud 400000 $18.87 86.2
Grok 4 Reasoning xAI 2000000 $19.67 87.8
Gemini 3 Pro Google DeepMind 2000000 $18.24 86.1
Gemini 3 Pro Pro Google DeepMind 200000 $19.80 87.3
Qwen3-Max Reasoning Alibaba Cloud 2000000 $18.12 85.9
o4 Turbo OpenAI 2000000 $19.34 86.6

Other benchmarks for Gemini 3 Pro Pro

BenchmarkScoreRankPercentileRelative
GPQA Diamond 81.4 38 94th
SWE-bench Verified 75.7 32 95th
HumanEval 95.0 2 100th
MATH-500 91.6 32 95th
AIME 2025 88.0 15 98th
LiveCodeBench 83.1 14 98th
IFEval 92.7 25 96th
TruthfulQA 87.6 27 96th
HellaSwag 93.6 17 97th
MMMU 83.2 20 97th
Arena Elo 1484.4 17 97th

FAQ

What score does Gemini 3 Pro Pro get on MMLU-Pro?

Gemini 3 Pro Pro scores 88.2 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Gemini 3 Pro Pro rank on MMLU-Pro?

It ranks #14 of 600 models, in the 98th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Gemini 3 Pro Pro 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 3 Pro Pro cost?

Gemini 3 Pro Pro costs $19.80 per million input tokens and $108.61 per million output tokens.

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