Coding · Hugging Face

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

SmolLM3 7B scores 47.7 on HumanEval, placing it #585 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
47.7
0–100 scale
Rank
#585
of 600
Percentile
3th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
49.1
points

Score distribution

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

GPT-5.2 Pro 96.8
Gemini 3 Pro Pro 95.0
o4 Max 94.6
Grok 4 Reasoning 93.8
Claude Opus 4.5 93.7
GPT-5.2 Max 93.6
Claude Opus 4.5 Pro 93.4
Grok 4 Max 93.4
GPT-5.2 Turbo 93.2
GPT-5.1 Reasoning 92.9

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Gemini 3 Pro Pro Google DeepMind 200000 $19.80 87.3
3 o4 Max OpenAI 2000000 $19.51 86.2
4 Grok 4 Reasoning xAI 2000000 $19.67 87.8
5 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
6 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
7 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
8 Grok 4 Max xAI 2000000 $19.70 86.6
9 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
10 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3

What this score means

On HumanEval, SmolLM3 7B sits at #585 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 49.1 points. The median model in this index scores 77.4, which puts SmolLM3 7B below the midpoint.

Hugging Face models average 56.7 on this benchmark. SmolLM3 7B is 9.0 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 56.7. SmolLM3 7B is 9.0 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 47.7 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 HumanEval. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
SmolLM3 8B Hugging Face 32768 $0.21 44.0
Phi-3.5 1.5B Microsoft 32768 $0.25 44.5
DBRX 1.5B Databricks 16384 $0.32 47.0
OLMo 2 1.5B Allen Institute for AI 16384 $0.28 44.0
SmolLM3 7B Hugging Face 16384 $0.19 44.3
Arctic 1.5B Snowflake 32768 $0.15 43.2
Molmo 1.5B Allen Institute for AI 8192 $0.21 42.8

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
MATH-500 44.4 579 4th
AIME 2025 26.6 589 2th
LiveCodeBench 30.7 582 3th
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 HumanEval?

SmolLM3 7B scores 47.7 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does SmolLM3 7B rank on HumanEval?

It ranks #585 of 600 models, in the 3rd percentile. The leader is GPT-5.2 Pro at 96.8.

Is SmolLM3 7B good at HumanEval?

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 HumanEval score calculated?

HumanEval 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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