Coding · Hugging Face

SmolLM3 Chat on LiveCodeBench: score, rank and what it means

SmolLM3 Chat scores 55.0 on LiveCodeBench, placing it #408 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
55.0
0–100 scale
Rank
#408
of 600
Percentile
32th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
30.1
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with SmolLM3 Chat 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 Chat sits at #408 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 30.1 points. The median model in this index scores 64.7, which puts SmolLM3 Chat below the midpoint.

Hugging Face models average 40.9 on this benchmark. SmolLM3 Chat is 14.1 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 Chat is 4.1 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 55.0 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 $1.61 per million input tokens, SmolLM3 Chat 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
Sonar Nano Perplexity 4096 $4.37 61.9
Embed 4 Turbo Cohere 4096 $5.13 64.0
Kimi K2 8B Moonshot AI 8192 $1.86 64.7
Nova Lite Mini Amazon 16384 $5.43 65.0
SmolLM3 Chat Hugging Face 16384 $1.61 62.1
Command A Nano Cohere 8192 $5.90 66.3
Nemotron Nano Chat NVIDIA 32768 $2.21 66.2

Other benchmarks for SmolLM3 Chat

BenchmarkScoreRankPercentileRelative
MMLU-Pro 68.7 409 32th
GPQA Diamond 57.5 433 28th
SWE-bench Verified 47.4 442 26th
HumanEval 63.6 454 24th
MATH-500 62.0 446 26th
AIME 2025 53.0 435 28th
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 LiveCodeBench?

SmolLM3 Chat scores 55.0 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does SmolLM3 Chat rank on LiveCodeBench?

It ranks #408 of 600 models, in the 32nd percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is SmolLM3 Chat 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 Chat cost?

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

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