Knowledge · Google DeepMind

Gemma 3 7B on MMLU-Pro: score, rank and what it means

Gemma 3 7B scores 60.8 on MMLU-Pro, placing it #514 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
60.8
0–100 scale
Rank
#514
of 600
Percentile
14th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
30.8
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with Gemma 3 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, Gemma 3 7B sits at #514 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 30.8 points. The median model in this index scores 76.1, which puts Gemma 3 7B below the midpoint.

Google DeepMind models average 80.4 on this benchmark. Gemma 3 7B is 19.6 points below that provider line, so it is a weaker result than the average Google DeepMind model.

Among small open-weight models, the average is 59.8. Gemma 3 7B is 1.0 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 60.8 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 $0.90 per million input tokens, Gemma 3 7B is below the median input price of $4.00 across the 600 models scored on MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Yi-Large 7B 01.AI 4096 $0.83 55.0
DBRX 8B Databricks 4096 $0.82 54.1
Seed-OSS 7B ByteDance 8192 $0.85 55.5
GLM-4.6 1.5B Zhipu AI 4096 $0.92 54.7
Gemma 3 7B Google DeepMind 32768 $0.90 55.9
Llama 3 Anyscale 8B Anyscale 32768 $0.97 57.3
Qwen3 1.5B Alibaba Cloud 4096 $0.84 53.5

Other benchmarks for Gemma 3 7B

BenchmarkScoreRankPercentileRelative
GPQA Diamond 54.0 482 20th
SWE-bench Verified 38.8 529 12th
HumanEval 61.2 482 20th
MATH-500 56.2 505 16th
AIME 2025 47.7 471 22th
LiveCodeBench 42.8 519 14th
IFEval 65.6 527 12th
TruthfulQA 59.3 538 10th
HellaSwag 72.2 491 18th
MMMU 56.8 474 21th
Arena Elo 1236.8 519 14th

FAQ

What score does Gemma 3 7B get on MMLU-Pro?

Gemma 3 7B scores 60.8 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does Gemma 3 7B rank on MMLU-Pro?

It ranks #514 of 600 models, in the 14th percentile. The leader is GPT-5.2 Pro at 91.6.

Is Gemma 3 7B good at MMLU-Pro?

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 MMLU-Pro score calculated?

MMLU-Pro is a knowledge 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 7B cost?

Gemma 3 7B costs $0.90 per million input tokens and $4.55 per million output tokens.

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