Mathematics · Google DeepMind

Gemini 3 Flash Max on MATH-500: score, rank and what it means

Gemini 3 Flash Max scores 88.6 on MATH-500, placing it #64 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
88.6
0–100 scale
Rank
#64
of 600
Percentile
89th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
8.1
points

Score distribution

The chart shows the top 10 models on MATH-500, with Gemini 3 Flash Max highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

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-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, Gemini 3 Flash Max sits at #64 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 8.1 points. The median model in this index scores 76.0, which puts Gemini 3 Flash Max above the midpoint.

Google DeepMind models average 81.8 on this benchmark. Gemini 3 Flash Max is 6.8 points above that provider line, so it is a stronger result than the average Google DeepMind model.

Among frontier models, the average is 90.8. Gemini 3 Flash Max is 2.2 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 88.6 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 $17.43 per million input tokens, Gemini 3 Flash Max is above the median input price of $4.00 across the 600 models scored on MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Claude 3.7 Sonnet Anthropic 200000 $14.91 81.6
GPT-4.1 Pro OpenAI 400000 $17.56 85.2
Claude Haiku 4.5 Max Anthropic 200000 $15.98 83.8
Grok 3 xAI 128000 $15.84 82.8
Gemini 3 Flash Max Google DeepMind 1000000 $17.43 85.0
Gemini 3 Pro Vision Google DeepMind 200000 $17.59 85.5
Claude Sonnet 4.5 Turbo Anthropic 1000000 $18.37 85.9

Other benchmarks for Gemini 3 Flash Max

BenchmarkScoreRankPercentileRelative
MMLU-Pro 87.8 19 97th
GPQA Diamond 80.9 45 93th
SWE-bench Verified 73.8 56 91th
HumanEval 88.5 64 89th
AIME 2025 86.7 22 96th
LiveCodeBench 78.3 62 90th
IFEval 91.3 48 92th
TruthfulQA 87.1 34 94th
HellaSwag 91.1 60 90th
MMMU 81.0 43 93th
Arena Elo 1448.5 77 87th

FAQ

What score does Gemini 3 Flash Max get on MATH-500?

Gemini 3 Flash Max scores 88.6 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Gemini 3 Flash Max rank on MATH-500?

It ranks #64 of 600 models, in the 89th percentile. The leader is GPT-5.2 Max at 96.7.

Is Gemini 3 Flash Max good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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 Flash Max cost?

Gemini 3 Flash Max costs $17.43 per million input tokens and $63.42 per million output tokens.

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