Coding · Hugging Face

SmolLM3 Instruct on HumanEval: score, rank and what it means

SmolLM3 Instruct scores 69.2 on HumanEval, placing it #408 of 600 models in the index. The benchmark average is 74.0 and the leader is GPT-5.2 Pro at 96.8.

Score
69.2
0–100 scale
Rank
#408
of 600
Percentile
32th
within the index
Benchmark avg
74.0
all models
Leader
96.8
GPT-5.2 Pro
Gap to leader
27.6
points

Score distribution

The chart shows the top 10 models on HumanEval, with SmolLM3 Instruct 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 Instruct sits at #408 of 600. The leader, GPT-5.2 Pro, scores 96.8, so the gap to the top is 27.6 points. The median model in this index scores 77.4, which puts SmolLM3 Instruct below the midpoint.

Hugging Face models average 56.7 on this benchmark. SmolLM3 Instruct is 12.5 points above that provider line, so it is a stronger result than the average Hugging Face model.

Among open-weight models, the average is 72.4. SmolLM3 Instruct is 3.2 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 69.2 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 $1.69 per million input tokens, SmolLM3 Instruct 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
StableLM 2 Instruct Stability AI 16384 $1.93 65.2
ERNIE 4.5 Nano Baidu 32768 $6.01 65.6
Embed 4 Cohere 32768 $4.79 63.8
Firefunction Mini Fireworks AI 32768 $4.63 63.2
SmolLM3 Instruct Hugging Face 8192 $1.69 63.6
Embed 4 Reasoning Cohere 4096 $5.50 65.3
Nova Pro Nano Amazon 8192 $5.44 65.4

Other benchmarks for SmolLM3 Instruct

BenchmarkScoreRankPercentileRelative
MMLU-Pro 67.3 428 29th
GPQA Diamond 58.4 423 30th
SWE-bench Verified 50.6 417 31th
MATH-500 67.0 409 32th
AIME 2025 54.4 419 30th
LiveCodeBench 56.1 397 34th
IFEval 74.0 406 32th
TruthfulQA 66.5 438 27th
HellaSwag 75.1 440 27th
MMMU 60.5 425 29th
Arena Elo 1297.8 423 30th

FAQ

What score does SmolLM3 Instruct get on HumanEval?

SmolLM3 Instruct scores 69.2 on HumanEval in this index. The benchmark average is 74.0 and the top score is 96.8.

How does SmolLM3 Instruct rank on HumanEval?

It ranks #408 of 600 models, in the 32nd percentile. The leader is GPT-5.2 Pro at 96.8.

Is SmolLM3 Instruct 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 Instruct cost?

SmolLM3 Instruct costs $1.69 per million input tokens and $8.67 per million output tokens.

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