Commonsense · Hugging Face

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

SmolLM3 7B scores 65.1 on HellaSwag, placing it #584 of 600 models in the index. The benchmark average is 81.4 and the leader is GPT-5.2 Max at 96.1.

Score
65.1
0–100 scale
Rank
#584
of 600
Percentile
3th
within the index
Benchmark avg
81.4
all models
Leader
96.1
GPT-5.2 Max
Gap to leader
31.0
points

Score distribution

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

GPT-5.2 Max 96.1
GPT-5.2 Turbo 95.5
GPT-5.2 Pro 95.3
Claude Opus 4.5 Pro 95.2
Claude Sonnet 4.5 Reasoning 95.2
Grok 4 Reasoning 95.2
GPT-5.2 Vision 94.6
Gemini 3 Pro Turbo 94.6
GPT-5.1 Reasoning 94.4
o4 Pro 94.4

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.2 Turbo OpenAI 1000000 $20.73 87.4
3 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
4 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
5 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
8 Gemini 3 Pro Turbo Google DeepMind 400000 $19.62 86.4
9 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
10 o4 Pro OpenAI 1000000 $19.37 87.3

What this score means

On HellaSwag, SmolLM3 7B sits at #584 of 600. The leader, GPT-5.2 Max, scores 96.1, so the gap to the top is 31.0 points. The median model in this index scores 83.6, which puts SmolLM3 7B below the midpoint.

Hugging Face models average 70.2 on this benchmark. SmolLM3 7B is 5.1 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 70.2. SmolLM3 7B is 5.1 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 65.1 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 HellaSwag. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Molmo 7B Allen Institute for AI 32768 $0.42 49.3
Llama 3 Hyperbolic 1.5B Hyperbolic 32768 $0.45 48.4
StableLM 2 7B Stability AI 8192 $0.28 44.3
Phi-3.5 1.5B Microsoft 32768 $0.25 44.5
SmolLM3 7B Hugging Face 16384 $0.19 44.3
Mixtral 1.5B Mistral AI 16384 $0.36 47.7
Zephyr 8B Hugging Face 8192 $0.22 43.0

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
HumanEval 47.7 585 3th
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
MMMU 40.3 594 1th
Arena Elo 1133.2 590 2th

FAQ

What score does SmolLM3 7B get on HellaSwag?

SmolLM3 7B scores 65.1 on HellaSwag in this index. The benchmark average is 81.4 and the top score is 96.1.

How does SmolLM3 7B rank on HellaSwag?

It ranks #584 of 600 models, in the 3rd percentile. The leader is GPT-5.2 Max at 96.1.

Is SmolLM3 7B good at HellaSwag?

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 HellaSwag score calculated?

HellaSwag is a commonsense 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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