Coding · Hugging Face

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

SmolLM3 scores 47.3 on SWE-bench Verified, placing it #444 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
47.3
0–100 scale
Rank
#444
of 600
Percentile
26th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
34.4
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with SmolLM3 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 sits at #444 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 34.4 points. The median model in this index scores 61.0, which puts SmolLM3 below the midpoint.

Hugging Face models average 37.7 on this benchmark. SmolLM3 is 9.6 points above that provider line, so it is a stronger result than the average Hugging Face model.

Among open-weight models, the average is 55.5. SmolLM3 is 8.2 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 47.3 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 $1.71 per million input tokens, SmolLM3 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 Chat EleutherAI 16384 $1.49 60.1
Fusion Mini OpenRouter 4096 $4.89 63.3
SmolLM3 Chat Hugging Face 16384 $1.61 62.1
QwQ 8B Alibaba Cloud 16384 $1.37 59.5
SmolLM3 Hugging Face 8192 $1.71 63.1
Pythia Instruct EleutherAI 8192 $1.41 60.8
ERNIE 4.0 Nano Baidu 32768 $4.68 62.1

Other benchmarks for SmolLM3

BenchmarkScoreRankPercentileRelative
MMLU-Pro 69.2 405 33th
GPQA Diamond 61.0 398 34th
HumanEval 69.5 403 33th
MATH-500 68.1 400 33th
AIME 2025 52.9 436 27th
LiveCodeBench 49.8 451 25th
IFEval 72.7 421 30th
TruthfulQA 67.9 415 31th
HellaSwag 77.7 405 33th
MMMU 58.3 454 24th
Arena Elo 1294.1 427 29th

FAQ

What score does SmolLM3 get on SWE-bench Verified?

SmolLM3 scores 47.3 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does SmolLM3 rank on SWE-bench Verified?

It ranks #444 of 600 models, in the 26th percentile. The leader is GPT-5.2 Pro at 81.7.

Is SmolLM3 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 cost?

SmolLM3 costs $1.71 per million input tokens and $8.86 per million output tokens.

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