Mathematics · Allen Institute for AI

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

OLMo 2 1.5B scores 41.9 on MATH-500, placing it #591 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
41.9
0–100 scale
Rank
#591
of 600
Percentile
2th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
54.8
points

Score distribution

The chart shows the top 10 models on MATH-500, with OLMo 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, OLMo 2 1.5B sits at #591 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 54.8 points. The median model in this index scores 76.0, which puts OLMo 2 1.5B below the midpoint.

Allen Institute for AI models average 60.7 on this benchmark. OLMo 2 1.5B is 18.8 points below that provider line, so it is a weaker result than the average Allen Institute for AI model.

Among small open-weight models, the average is 53.7. OLMo 2 1.5B is 11.8 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 41.9 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 $0.28 per million input tokens, OLMo 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
GPT-NeoX 7B EleutherAI 8192 $0.20 42.4
StableLM 2 7B Stability AI 8192 $0.28 44.3
Pythia 7B EleutherAI 8192 $0.10 40.7
GPT-NeoX 8B EleutherAI 16384 $0.25 43.7
OLMo 2 1.5B Allen Institute for AI 16384 $0.28 44.0
Nemotron Nano 1.5B NVIDIA 8192 $0.10 41.5
Zephyr 8B Hugging Face 8192 $0.22 43.0

Other benchmarks for OLMo 2 1.5B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 51.2 588 2th
GPQA Diamond 40.7 582 3th
SWE-bench Verified 26.3 592 1th
HumanEval 48.3 584 3th
AIME 2025 29.2 585 3th
LiveCodeBench 29.4 584 3th
IFEval 55.4 591 2th
TruthfulQA 50.5 590 2th
HellaSwag 64.3 588 2th
MMMU 46.4 577 4th
Arena Elo 1142.8 586 2th

FAQ

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

OLMo 2 1.5B scores 41.9 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

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

It ranks #591 of 600 models, in the 2nd percentile. The leader is GPT-5.2 Max at 96.7.

Is OLMo 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 OLMo 2 1.5B cost?

OLMo 2 1.5B costs $0.28 per million input tokens and $1.41 per million output tokens.

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