Mathematics · Hugging Face

SmolLM3 8B on MATH-500: score, rank and what it means

SmolLM3 8B scores 44.4 on MATH-500, placing it #580 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
44.4
0–100 scale
Rank
#580
of 600
Percentile
3th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
52.3
points

Score distribution

The chart shows the top 10 models on MATH-500, with SmolLM3 8B highlighted. Longer bars mean higher scores.

GPT-5.2 Max 96.7
GPT-5.1 Reasoning 95.9
GPT-5.1 Pro 95.1
o4 Reasoning 94.8
Grok 4 Max 94.6
Grok 4 Reasoning 94.4
Claude Opus 4.5 Max 94.2
Claude Opus 4.5 93.7
Gemini 3 Pro Reasoning 93.3
Claude Opus 4.5 Turbo 93.2

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
2 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
3 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
4 o4 Reasoning OpenAI 1000000 $19.69 87.5
5 Grok 4 Max xAI 2000000 $19.70 86.6
6 Grok 4 Reasoning xAI 2000000 $19.67 87.8
7 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
8 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
9 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
10 Claude Opus 4.5 Turbo Anthropic 2000000 $19.57 85.7

What this score means

On MATH-500, SmolLM3 8B sits at #580 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 52.3 points. The median model in this index scores 76.0, which puts SmolLM3 8B below the midpoint.

Hugging Face models average 53.8 on this benchmark. SmolLM3 8B is 9.4 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 53.7. SmolLM3 8B 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 44.4 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 $0.21 per million input tokens, SmolLM3 8B is below the median input price of $4.00 across the 600 models scored on MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Gemma 3 1.5B Google DeepMind 32768 $0.40 48.9
Yi-Large 1.5B 01.AI 8192 $0.42 46.8
StableLM 2 8B Stability AI 32768 $0.38 47.0
SmolLM3 7B Hugging Face 16384 $0.19 44.3
SmolLM3 8B Hugging Face 32768 $0.21 44.0
Mixtral Turbo 1.5B Together AI 4096 $0.31 47.6
Mixtral Groq 1.5B Groq 4096 $0.34 46.1

Other benchmarks for SmolLM3 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 51.2 589 2th
GPQA Diamond 38.9 589 2th
SWE-bench Verified 27.8 586 2th
HumanEval 49.0 581 3th
AIME 2025 26.2 591 2th
LiveCodeBench 31.3 581 3th
IFEval 56.3 589 2th
TruthfulQA 50.6 589 2th
HellaSwag 66.2 576 4th
MMMU 41.8 590 2th
Arena Elo 1153.0 584 3th

FAQ

What score does SmolLM3 8B get on MATH-500?

SmolLM3 8B scores 44.4 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does SmolLM3 8B rank on MATH-500?

It ranks #580 of 600 models, in the 3rd percentile. The leader is GPT-5.2 Max at 96.7.

Is SmolLM3 8B good at MATH-500?

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 MATH-500 score calculated?

MATH-500 is a mathematics 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 8B cost?

SmolLM3 8B costs $0.21 per million input tokens and $0.76 per million output tokens.

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