Coding · Hugging Face

SmolLM3 1.5B on SWE-bench Verified: score, rank and what it means

SmolLM3 1.5B scores 18.4 on SWE-bench Verified, placing it #599 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
18.4
0–100 scale
Rank
#599
of 600
Percentile
1th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
63.3
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with SmolLM3 1.5B highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 81.7
Claude Opus 4.5 Pro 81.1
GPT-5.2 Max 80.5
Claude Sonnet 4.5 Max 80.2
GPT-5.2 80.2
GPT-5.1 Pro 80.1
o4 Max 79.8
Claude Sonnet 4.5 Reasoning 79.6
Claude Opus 4.5 Max 79.5
Claude Opus 4.5 Reasoning 79.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
3 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
4 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 o4 Max OpenAI 2000000 $19.51 86.2
8 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2

What this score means

On SWE-bench Verified, SmolLM3 1.5B sits at #599 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 63.3 points. The median model in this index scores 61.0, which puts SmolLM3 1.5B below the midpoint.

Hugging Face models average 37.7 on this benchmark. SmolLM3 1.5B is 19.3 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 39.0. SmolLM3 1.5B is 20.6 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 18.4 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 SWE-bench Verified. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Zephyr 7B Hugging Face 32768 $0.23 42.5
Pythia 1.5B EleutherAI 4096 $0.10 35.8
StableLM 2 1.5B Stability AI 16384 $0.13 38.3
Zephyr 1.5B Hugging Face 32768 $0.10 38.0
SmolLM3 1.5B Hugging Face 8192 $0.04 36.8
GPT-NeoX 1.5B EleutherAI 32768 $0.06 36.4

Other benchmarks for SmolLM3 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 46.7 599 1th
GPQA Diamond 31.9 599 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 SWE-bench Verified?

SmolLM3 1.5B scores 18.4 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does SmolLM3 1.5B rank on SWE-bench Verified?

It ranks #599 of 600 models, in the 1st percentile. The leader is GPT-5.2 Pro at 81.7.

Is SmolLM3 1.5B good at SWE-bench Verified?

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 SWE-bench Verified score calculated?

SWE-bench Verified 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 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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