Mathematics · Google DeepMind

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

Gemma 3 scores 75.7 on MATH-500, placing it #309 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
75.7
0–100 scale
Rank
#309
of 600
Percentile
49th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
21.0
points

Score distribution

The chart shows the top 10 models on MATH-500, with Gemma 3 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, Gemma 3 sits at #309 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 21.0 points. The median model in this index scores 76.0, which puts Gemma 3 below the midpoint.

Google DeepMind models average 81.8 on this benchmark. Gemma 3 is 6.1 points below that provider line, so it is a weaker result than the average Google DeepMind model.

Among multimodal models, the average is 81.3. Gemma 3 is 5.6 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 75.7 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 $3.68 per million input tokens, Gemma 3 is below 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
Llama 3 Modal Base Modal 16384 $3.21 72.2
Mixtral Chat Mistral AI 65536 $3.30 72.6
Nova Pro Mini Amazon 16384 $7.74 70.6
DBRX Instruct Databricks 8192 $3.21 72.4
Gemma 3 Google DeepMind 65536 $3.68 73.6
Llama 3 Replicate Base Replicate 65536 $3.15 72.1
Llama 3 Lambda Chat Lambda 32768 $3.73 74.7

Other benchmarks for Gemma 3

BenchmarkScoreRankPercentileRelative
MMLU-Pro 75.1 330 45th
GPQA Diamond 71.5 230 62th
SWE-bench Verified 60.0 328 45th
HumanEval 76.6 315 48th
AIME 2025 69.2 274 54th
LiveCodeBench 65.4 285 53th
IFEval 82.0 279 54th
TruthfulQA 78.6 232 61th
HellaSwag 83.7 290 52th
MMMU 72.1 239 60th
Arena Elo 1371.5 312 48th

FAQ

What score does Gemma 3 get on MATH-500?

Gemma 3 scores 75.7 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Gemma 3 rank on MATH-500?

It ranks #309 of 600 models, in the 49th percentile. The leader is GPT-5.2 Max at 96.7.

Is Gemma 3 good at MATH-500?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. 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 Gemma 3 cost?

Gemma 3 costs $3.68 per million input tokens and $14.67 per million output tokens.

Related