Mathematics · Google DeepMind

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

Gemma 3 Instruct scores 78.9 on MATH-500, placing it #238 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
78.9
0–100 scale
Rank
#238
of 600
Percentile
60th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
17.8
points

Score distribution

The chart shows the top 10 models on MATH-500, with Gemma 3 Instruct 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 Instruct sits at #238 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 17.8 points. The median model in this index scores 76.0, which puts Gemma 3 Instruct above the midpoint.

Google DeepMind models average 81.8 on this benchmark. Gemma 3 Instruct is 2.9 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 Instruct is 2.4 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 78.9 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 $3.72 per million input tokens, Gemma 3 Instruct 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 Chat Modal 65536 $3.55 73.3
MiniMax-Text MiniMax 32768 $4.44 77.0
Phi-4 Microsoft 200000 $3.96 75.4
Gemini 3 Flash Mini Google DeepMind 200000 $10.71 76.0
Gemma 3 Instruct Google DeepMind 128000 $3.72 74.1
Llama 3.1 Chat Meta AI 32768 $3.82 75.3
Llama 3.3 Groq Groq 32768 $3.98 76.8

Other benchmarks for Gemma 3 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 75.4 321 47th
GPQA Diamond 69.2 289 52th
SWE-bench Verified 66.0 194 68th
HumanEval 80.5 220 63th
AIME 2025 67.4 306 49th
LiveCodeBench 64.4 308 49th
IFEval 81.1 308 49th
TruthfulQA 75.7 314 48th
HellaSwag 84.1 277 54th
MMMU 72.4 232 61th
Arena Elo 1377.2 283 53th

FAQ

What score does Gemma 3 Instruct get on MATH-500?

Gemma 3 Instruct scores 78.9 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does Gemma 3 Instruct rank on MATH-500?

It ranks #238 of 600 models, in the 60th percentile. The leader is GPT-5.2 Max at 96.7.

Is Gemma 3 Instruct 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 Gemma 3 Instruct cost?

Gemma 3 Instruct costs $3.72 per million input tokens and $14.33 per million output tokens.

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