Reasoning · Google DeepMind

Gemma 3 1.5B on GPQA Diamond: score, rank and what it means

Gemma 3 1.5B scores 44.2 on GPQA Diamond, placing it #570 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
44.2
0–100 scale
Rank
#570
of 600
Percentile
5th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
42.8
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with Gemma 3 1.5B highlighted. Longer bars mean higher scores.

GPT-5.2 Reasoning 87.0
GPT-5.1 Max 86.4
Claude Opus 4.5 Pro 86.0
GPT-5.1 Reasoning 85.6
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.2 84.9
o4 Turbo 84.8
Claude Opus 4.5 Max 84.6
Grok 4 Turbo 84.5
Claude Sonnet 4.5 Max 84.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 GPT-5.2 OpenAI 2000000 $19.71 88.0
7 o4 Turbo OpenAI 2000000 $19.34 86.6
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 Grok 4 Turbo xAI 1000000 $19.21 86.7
10 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2

What this score means

On GPQA Diamond, Gemma 3 1.5B sits at #570 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 42.8 points. The median model in this index scores 68.8, which puts Gemma 3 1.5B below the midpoint.

Google DeepMind models average 73.4 on this benchmark. Gemma 3 1.5B is 29.2 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 49.3. Gemma 3 1.5B is 5.1 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 44.2 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 $0.40 per million input tokens, Gemma 3 1.5B is below the median input price of $4.00 across the 600 models scored on GPQA Diamond. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Seed-OSS 1.5B ByteDance 4096 $0.45 49.8
Arctic 7B Snowflake 8192 $0.49 50.3
Llama 3 Baseten 1.5B Baseten 4096 $0.42 48.2
Mistral Small 3 1.5B Mistral AI 32768 $0.42 49.2
Gemma 3 1.5B Google DeepMind 32768 $0.40 48.9
Command R+ 1.5B Cohere 32768 $0.51 50.0
Llama 3.1 Turbo 1.5B Together AI 16384 $0.46 49.8

Other benchmarks for Gemma 3 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 54.0 576 4th
SWE-bench Verified 32.6 573 5th
HumanEval 53.0 555 8th
MATH-500 46.0 576 4th
AIME 2025 39.2 546 9th
LiveCodeBench 34.0 573 5th
IFEval 62.3 552 8th
TruthfulQA 55.9 568 5th
HellaSwag 68.8 548 9th
MMMU 48.3 561 7th
Arena Elo 1193.8 561 7th

FAQ

What score does Gemma 3 1.5B get on GPQA Diamond?

Gemma 3 1.5B scores 44.2 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does Gemma 3 1.5B rank on GPQA Diamond?

It ranks #570 of 600 models, in the 5th percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is Gemma 3 1.5B good at GPQA Diamond?

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 GPQA Diamond score calculated?

GPQA Diamond is a reasoning 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 1.5B cost?

Gemma 3 1.5B costs $0.40 per million input tokens and $1.82 per million output tokens.

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