Mathematics · Stability AI

StableLM 2 1.5B on MATH-500: score, rank and what it means

StableLM 2 1.5B scores 34.3 on MATH-500, placing it #599 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
34.3
0–100 scale
Rank
#599
of 600
Percentile
1th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
62.4
points

Score distribution

The chart shows the top 10 models on MATH-500, with StableLM 2 1.5B 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, StableLM 2 1.5B sits at #599 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 62.4 points. The median model in this index scores 76.0, which puts StableLM 2 1.5B below the midpoint.

Stability AI models average 55.6 on this benchmark. StableLM 2 1.5B is 21.3 points below that provider line, so it is a weaker result than the average Stability AI model.

Among small open-weight models, the average is 53.7. StableLM 2 1.5B is 19.4 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 34.3 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 $0.13 per million input tokens, StableLM 2 1.5B 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
Pythia 8B EleutherAI 32768 $0.16 41.4
SmolLM3 1.5B Hugging Face 8192 $0.04 36.8
GPT-NeoX 1.5B EleutherAI 32768 $0.06 36.4
Zephyr 1.5B Hugging Face 32768 $0.10 38.0
StableLM 2 1.5B Stability AI 16384 $0.13 38.3
Pythia 1.5B EleutherAI 4096 $0.10 35.8

Other benchmarks for StableLM 2 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 48.2 597 1th
GPQA Diamond 32.7 597 1th
SWE-bench Verified 19.4 597 1th
HumanEval 39.5 598 1th
AIME 2025 24.8 595 1th
LiveCodeBench 22.2 597 1th
IFEval 50.8 598 1th
TruthfulQA 49.8 593 1th
HellaSwag 59.4 597 1th
MMMU 39.8 595 1th
Arena Elo 1103.1 598 1th

FAQ

What score does StableLM 2 1.5B get on MATH-500?

StableLM 2 1.5B scores 34.3 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does StableLM 2 1.5B rank on MATH-500?

It ranks #599 of 600 models, in the 1st percentile. The leader is GPT-5.2 Max at 96.7.

Is StableLM 2 1.5B 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 StableLM 2 1.5B cost?

StableLM 2 1.5B costs $0.13 per million input tokens and $0.46 per million output tokens.

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