Mathematics · Google DeepMind

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

Gemini 3 Flash scores 89.0 on MATH-500, placing it #59 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
89.0
0–100 scale
Rank
#59
of 600
Percentile
90th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
7.7
points

Score distribution

The chart shows the top 10 models on MATH-500, with Gemini 3 Flash 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 sits at #59 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 7.7 points. The median model in this index scores 76.0, which puts Gemini 3 Flash above the midpoint.

Google DeepMind models average 81.8 on this benchmark. Gemini 3 Flash is 7.2 points above that provider line, so it is a stronger result than the average Google DeepMind model.

Among multimodal models, the average is 81.3. Gemini 3 Flash is 7.7 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 89.0 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 $15.67 per million input tokens, Gemini 3 Flash 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
DeepSeek-R1 DeepSeek 128000 $5.83 82.8
DeepSeek-R1 Chat DeepSeek 400000 $5.62 82.4
GPT-4.1 Reasoning OpenAI 1000000 $16.97 83.8
GPT-5.1 Vision OpenAI 400000 $17.76 84.8
Gemini 3 Flash Google DeepMind 128000 $15.67 83.6
Claude 3.7 Sonnet Anthropic 200000 $14.91 81.6
GPT-4.1 Pro OpenAI 400000 $17.56 85.2

Other benchmarks for Gemini 3 Flash

BenchmarkScoreRankPercentileRelative
MMLU-Pro 83.7 87 86th
GPQA Diamond 80.3 52 91th
SWE-bench Verified 72.5 66 89th
HumanEval 86.2 100 83th
AIME 2025 84.5 44 93th
LiveCodeBench 79.3 51 92th
IFEval 91.0 54 91th
TruthfulQA 84.8 66 89th
HellaSwag 89.8 91 85th
MMMU 78.2 92 85th
Arena Elo 1450.7 71 88th

FAQ

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

Gemini 3 Flash scores 89.0 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Gemini 3 Flash rank on MATH-500?

It ranks #59 of 600 models, in the 90th percentile. The leader is GPT-5.2 Max at 96.7.

Is Gemini 3 Flash 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 cost?

Gemini 3 Flash costs $15.67 per million input tokens and $70.15 per million output tokens.

Related