Coding · Hugging Face

SmolLM3 7B on LiveCodeBench: score, rank and what it means

SmolLM3 7B scores 30.7 on LiveCodeBench, placing it #582 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.

Score
30.7
0–100 scale
Rank
#582
of 600
Percentile
3th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
54.4
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with SmolLM3 7B highlighted. Longer bars mean higher scores.

Claude Sonnet 4.5 Reasoning 85.1
Grok 4 Reasoning 85.1
Claude Opus 4.5 85.0
GPT-5.2 Max 84.8
Grok 4 Turbo 84.7
GPT-5.1 Turbo 84.6
GPT-5.2 Pro 84.6
GPT-5.2 Reasoning 84.6
Claude Opus 4.5 Pro 84.1
Gemini 3 Pro Max 83.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
2 Grok 4 Reasoning xAI 2000000 $19.67 87.8
3 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 Grok 4 Turbo xAI 1000000 $19.21 86.7
6 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1
7 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
8 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
9 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On LiveCodeBench, SmolLM3 7B sits at #582 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 54.4 points. The median model in this index scores 64.7, which puts SmolLM3 7B below the midpoint.

Hugging Face models average 40.9 on this benchmark. SmolLM3 7B is 10.2 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 41.2. SmolLM3 7B is 10.5 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 30.7 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 LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Mixtral Groq 1.5B Groq 4096 $0.34 46.1
Nemotron Nano 7B NVIDIA 8192 $0.35 47.5
Llama 3 Baseten 1.5B Baseten 4096 $0.42 48.2
SmolLM3 8B Hugging Face 32768 $0.21 44.0
SmolLM3 7B Hugging Face 16384 $0.19 44.3
StableLM 2 8B Stability AI 32768 $0.38 47.0
OLMo 2 1.5B Allen Institute for AI 16384 $0.28 44.0

Other benchmarks for SmolLM3 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 53.6 577 4th
GPQA Diamond 41.8 578 4th
SWE-bench Verified 27.6 587 2th
HumanEval 47.7 585 3th
MATH-500 44.4 579 4th
AIME 2025 26.6 589 2th
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 LiveCodeBench?

SmolLM3 7B scores 30.7 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does SmolLM3 7B rank on LiveCodeBench?

It ranks #582 of 600 models, in the 3rd percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is SmolLM3 7B good at LiveCodeBench?

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 LiveCodeBench score calculated?

LiveCodeBench 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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