Coding · Hugging Face

SmolLM3 on LiveCodeBench: score, rank and what it means

SmolLM3 scores 49.8 on LiveCodeBench, placing it #451 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
49.8
0–100 scale
Rank
#451
of 600
Percentile
25th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
35.3
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with SmolLM3 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 sits at #451 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 35.3 points. The median model in this index scores 64.7, which puts SmolLM3 below the midpoint.

Hugging Face models average 40.9 on this benchmark. SmolLM3 is 8.9 points above that provider line, so it is a stronger result than the average Hugging Face model.

Among open-weight models, the average is 59.1. SmolLM3 is 9.3 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 49.8 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 LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
MiniMax-M2 7B MiniMax 8192 $1.44 60.8
MiniMax-M2 8B MiniMax 32768 $1.65 61.7
Zephyr Instruct Hugging Face 4096 $1.66 62.4
Nova Lite Nano Amazon 8192 $3.29 59.5
SmolLM3 Hugging Face 8192 $1.71 63.1
Llama 4 Scout 8B Meta AI 8192 $1.46 61.2
Codestral 8B Mistral AI 4096 $1.18 59.0

Other benchmarks for SmolLM3

BenchmarkScoreRankPercentileRelative
MMLU-Pro 69.2 405 33th
GPQA Diamond 61.0 398 34th
SWE-bench Verified 47.3 444 26th
HumanEval 69.5 403 33th
MATH-500 68.1 400 33th
AIME 2025 52.9 436 27th
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 LiveCodeBench?

SmolLM3 scores 49.8 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does SmolLM3 rank on LiveCodeBench?

It ranks #451 of 600 models, in the 25th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is SmolLM3 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 cost?

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

Related