Reasoning · Hugging Face

SmolLM3 1.5B on GPQA Diamond: score, rank and what it means

SmolLM3 1.5B scores 31.9 on GPQA Diamond, placing it #599 of 600 models in the index. The benchmark average is 65.6 and the leader is GPT-5.2 Reasoning at 87.0.

Score
31.9
0–100 scale
Rank
#599
of 600
Percentile
1th
within the index
Benchmark avg
65.6
all models
Leader
87.0
GPT-5.2 Reasoning
Gap to leader
55.1
points

Score distribution

The chart shows the top 10 models on GPQA Diamond, with SmolLM3 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, SmolLM3 1.5B sits at #599 of 600. The leader, GPT-5.2 Reasoning, scores 87.0, so the gap to the top is 55.1 points. The median model in this index scores 68.8, which puts SmolLM3 1.5B below the midpoint.

Hugging Face models average 49.3 on this benchmark. SmolLM3 1.5B is 17.4 points below that provider line, so it is a weaker result than the average Hugging Face model.

Among small open-weight models, the average is 49.3. SmolLM3 1.5B is 17.4 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 31.9 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 $0.040 per million input tokens, SmolLM3 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
Zephyr 1.5B Hugging Face 32768 $0.10 38.0
Pythia 7B EleutherAI 8192 $0.10 40.7
StableLM 2 1.5B Stability AI 16384 $0.13 38.3
GPT-NeoX 1.5B EleutherAI 32768 $0.06 36.4
SmolLM3 1.5B Hugging Face 8192 $0.04 36.8
Pythia 1.5B EleutherAI 4096 $0.10 35.8

Other benchmarks for SmolLM3 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 46.7 599 1th
SWE-bench Verified 18.4 599 1th
HumanEval 39.8 597 1th
MATH-500 37.7 596 1th
AIME 2025 21.7 597 1th
LiveCodeBench 20.0 600 1th
IFEval 50.2 599 1th
TruthfulQA 44.2 600 1th
HellaSwag 58.1 599 1th
MMMU 35.8 599 1th
Arena Elo 1103.0 599 1th

FAQ

What score does SmolLM3 1.5B get on GPQA Diamond?

SmolLM3 1.5B scores 31.9 on GPQA Diamond in this index. The benchmark average is 65.6 and the top score is 87.0.

How does SmolLM3 1.5B rank on GPQA Diamond?

It ranks #599 of 600 models, in the 1st percentile. The leader is GPT-5.2 Reasoning at 87.0.

Is SmolLM3 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 SmolLM3 1.5B cost?

SmolLM3 1.5B costs $0.040 per million input tokens and $0.17 per million output tokens.

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