Coding · Hugging Face

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

SmolLM3 Chat scores 47.4 on SWE-bench Verified, placing it #442 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
47.4
0–100 scale
Rank
#442
of 600
Percentile
26th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
34.3
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with SmolLM3 Chat 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 Chat sits at #442 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 34.3 points. The median model in this index scores 61.0, which puts SmolLM3 Chat below the midpoint.

Hugging Face models average 37.7 on this benchmark. SmolLM3 Chat is 9.7 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 Chat is 8.1 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 47.4 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 $1.61 per million input tokens, SmolLM3 Chat 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
Magistral 8B Mistral AI 4096 $1.33 60.0
Nova Lite Nano Amazon 8192 $3.29 59.5
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

Other benchmarks for SmolLM3 Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 68.7 409 32th
GPQA Diamond 57.5 433 28th
HumanEval 63.6 454 24th
MATH-500 62.0 446 26th
AIME 2025 53.0 435 28th
LiveCodeBench 55.0 408 32th
IFEval 72.6 424 29th
TruthfulQA 66.4 439 27th
HellaSwag 76.1 427 29th
MMMU 60.3 426 29th
Arena Elo 1293.9 428 29th

FAQ

What score does SmolLM3 Chat get on SWE-bench Verified?

SmolLM3 Chat scores 47.4 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does SmolLM3 Chat rank on SWE-bench Verified?

It ranks #442 of 600 models, in the 26th percentile. The leader is GPT-5.2 Pro at 81.7.

Is SmolLM3 Chat 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 Chat cost?

SmolLM3 Chat costs $1.61 per million input tokens and $7.69 per million output tokens.

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