Coding · Hugging Face

SmolLM3 1.5B on LiveCodeBench: score, rank and what it means

SmolLM3 1.5B scores 20.0 on LiveCodeBench, placing it #600 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
20.0
0–100 scale
Rank
#600
of 600
Percentile
1th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
65.1
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with SmolLM3 1.5B 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 1.5B sits at #600 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 65.1 points. The median model in this index scores 64.7, which puts SmolLM3 1.5B below the midpoint.

Hugging Face models average 40.9 on this benchmark. SmolLM3 1.5B is 20.9 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 1.5B is 21.2 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 20.0 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 LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
Grok 4 Reasoning xAI 2000000 $19.67 87.8
Claude Opus 4.5 Anthropic 400000 $19.42 87.7
GPT-5.2 Max OpenAI 1000000 $21.39 89.2
Grok 4 Turbo xAI 1000000 $19.21 86.7
GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1

Other benchmarks for SmolLM3 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 46.7 599 1th
GPQA Diamond 31.9 599 1th
SWE-bench Verified 18.4 599 1th
HumanEval 39.8 597 1th
MATH-500 37.7 596 1th
AIME 2025 21.7 597 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 LiveCodeBench?

SmolLM3 1.5B scores 20.0 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does SmolLM3 1.5B rank on LiveCodeBench?

It ranks #600 of 600 models, in the 1st percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is SmolLM3 1.5B 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 1.5B cost?

SmolLM3 1.5B costs $0.040 per million input tokens and $0.17 per million output tokens.

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