Reasoning · Google DeepMind

Gemini 3 Pro on GPQA Diamond: score, rank and what it means

Gemini 3 Pro scores 79.0 on GPQA Diamond, placing it #72 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
79.0
0–100 scale
Rank
#72
of 600
Percentile
88th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
8.0
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Gemini 3 Pro highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, Gemini 3 Pro sits at #72 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 8.0 points. The median model in this index scores 68.8, which puts Gemini 3 Pro above the midpoint.

Google DeepMind models average 73.4 on this benchmark. Gemini 3 Pro is 5.6 points above that provider line, so it is a stronger result than the average Google DeepMind model.

Among frontier models, the average is 81.5. Gemini 3 Pro is 2.5 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 79.0 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 $18.24 per million input tokens, Gemini 3 Pro is above the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
GPT-4.1 Vision OpenAI 1000000 $14.88 82.0
Grok 4 Pro xAI 1000000 $19.00 85.4
Command A Pro Cohere 200000 $14.28 81.3
Grok 3 Turbo xAI 128000 $15.97 83.1
Gemini 3 Pro Google DeepMind 2000000 $18.24 86.1
Sonar Pro Max Perplexity 128000 $14.01 81.1
GPT-5.1 Vision OpenAI 400000 $17.76 84.8

Other benchmarks for Gemini 3 Pro

BenchmarkScoreRankPercentileRelative
MMLU-Pro 88.2 13 98th
SWE-bench Verified 78.5 12 98th
HumanEval 91.8 26 96th
MATH-500 89.9 49 92th
AIME 2025 84.3 46 92th
LiveCodeBench 83.3 13 98th
IFEval 93.7 14 98th
TruthfulQA 88.8 13 98th
HellaSwag 91.3 53 91th
MMMU 78.6 82 86th
Arena Elo 1460.7 52 91th

FAQ

What score does Gemini 3 Pro get on GPQA Diamond?

Gemini 3 Pro scores 79.0 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Gemini 3 Pro rank on GPQA Diamond?

It ranks #72 of 600 models, in the 88th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Gemini 3 Pro good at GPQA Diamond?

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 GPQA Diamond score calculated?

GPQA Diamond is a reasoning 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 cost?

Gemini 3 Pro costs $18.24 per million input tokens and $82.93 per million output tokens.

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