Mathematics · Hugging Face

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

SmolLM3 Chat scores 62.0 on MATH-500, placing it #446 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
62.0
0–100 scale
Rank
#446
of 600
Percentile
26th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
34.7
points

Score distribution

The chart shows the top 10 models on MATH-500, with SmolLM3 Chat 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 Chat sits at #446 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 34.7 points. The median model in this index scores 76.0, which puts SmolLM3 Chat below the midpoint.

Hugging Face models average 53.8 on this benchmark. SmolLM3 Chat is 8.2 points above that provider line, so it is a stronger result than the average Hugging Face model.

Among open-weight models, the average is 70.8. SmolLM3 Chat is 8.8 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 62.0 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 MATH-500. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Auto Mini OpenRouter 4096 $4.24 61.6
Kimi K1.5 8B Moonshot AI 8192 $1.54 62.2
GLM-4.6 8B Zhipu AI 8192 $1.69 63.1
Llama 3.3 7B Meta AI 8192 $1.18 57.8
SmolLM3 Chat Hugging Face 16384 $1.61 62.1
Qwen3-Coder 7B Alibaba Cloud 32768 $1.24 59.6
Reka Flash Nano Reka AI 16384 $3.93 61.0

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
AIME 2025 53.0 435 28th
LiveCodeBench 55.0 408 32th
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 MATH-500?

SmolLM3 Chat scores 62.0 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does SmolLM3 Chat rank on MATH-500?

It ranks #446 of 600 models, in the 26th percentile. The leader is GPT-5.2 Max at 96.7.

Is SmolLM3 Chat 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 Chat cost?

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

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