Coding · Hugging Face

SmolLM3 7B on SWE-bench Verified: score, rank and what it means

SmolLM3 7B scores 27.6 on SWE-bench Verified, placing it #587 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
27.6
0–100 scale
Rank
#587
of 600
Percentile
2th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
54.1
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with SmolLM3 7B 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 7B sits at #587 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 54.1 points. The median model in this index scores 61.0, which puts SmolLM3 7B below the midpoint.

Hugging Face models average 37.7 on this benchmark. SmolLM3 7B is 10.1 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 7B is 11.4 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 27.6 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 $0.19 per million input tokens, SmolLM3 7B 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
GPT-NeoX 8B EleutherAI 16384 $0.25 43.7
Molmo 1.5B Allen Institute for AI 8192 $0.21 42.8
Phi-3.5 1.5B Microsoft 32768 $0.25 44.5
SmolLM3 8B Hugging Face 32768 $0.21 44.0
SmolLM3 7B Hugging Face 16384 $0.19 44.3
Pythia 8B EleutherAI 32768 $0.16 41.4
Pythia 7B EleutherAI 8192 $0.10 40.7

Other benchmarks for SmolLM3 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 53.6 577 4th
GPQA Diamond 41.8 578 4th
HumanEval 47.7 585 3th
MATH-500 44.4 579 4th
AIME 2025 26.6 589 2th
LiveCodeBench 30.7 582 3th
IFEval 57.7 584 3th
TruthfulQA 52.1 586 2th
HellaSwag 65.1 584 3th
MMMU 40.3 594 1th
Arena Elo 1133.2 590 2th

FAQ

What score does SmolLM3 7B get on SWE-bench Verified?

SmolLM3 7B scores 27.6 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does SmolLM3 7B rank on SWE-bench Verified?

It ranks #587 of 600 models, in the 2nd percentile. The leader is GPT-5.2 Pro at 81.7.

Is SmolLM3 7B 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 7B cost?

SmolLM3 7B costs $0.19 per million input tokens and $1.03 per million output tokens.

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