Coding · Google DeepMind

Gemma 3 7B on HumanEval: score, rank and what it means

Gemma 3 7B scores 61.2 on HumanEval, placing it #482 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
61.2
0–100 scale
Rank
#482
of 600
Percentile
20th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
35.6
points

Score distribution

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

GPT-5.2 Pro 96.8
Gemini 3 Pro Pro 95.0
o4 Max 94.6
Grok 4 Reasoning 93.8
Claude Opus 4.5 93.7
GPT-5.2 Max 93.6
Claude Opus 4.5 Pro 93.4
Grok 4 Max 93.4
GPT-5.2 Turbo 93.2
GPT-5.1 Reasoning 92.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Gemini 3 Pro Pro Google DeepMind 200000 $19.80 87.3
3 o4 Max OpenAI 2000000 $19.51 86.2
4 Grok 4 Reasoning xAI 2000000 $19.67 87.8
5 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
6 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
7 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
8 Grok 4 Max xAI 2000000 $19.70 86.6
9 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
10 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3

What this score means

On HumanEval, Gemma 3 7B sits at #482 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 35.6 points. The median model in this index scores 77.4, which puts Gemma 3 7B below the midpoint.

Google DeepMind models average 82.4 on this benchmark. Gemma 3 7B is 21.2 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 56.7. Gemma 3 7B is 4.5 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 61.2 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 HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Mistral Small 3 8B Mistral AI 8192 $0.99 57.2
Phi-4 7B Microsoft 8192 $0.91 56.8
Seed-OSS 8B ByteDance 8192 $1.05 57.1
Yi-Large 8B 01.AI 32768 $0.88 56.1
Gemma 3 7B Google DeepMind 32768 $0.90 55.9
Llama 4 Scout 7B Meta AI 32768 $1.30 60.0
Nemotron 4 8B NVIDIA 4096 $1.06 57.9

Other benchmarks for Gemma 3 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 60.8 514 14th
GPQA Diamond 54.0 482 20th
SWE-bench Verified 38.8 529 12th
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 HumanEval?

Gemma 3 7B scores 61.2 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does Gemma 3 7B rank on HumanEval?

It ranks #482 of 600 models, in the 20th percentile. The leader is GPT-5.2 Pro at 96.8.

Is Gemma 3 7B good at HumanEval?

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 HumanEval score calculated?

HumanEval is a coding 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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