Mathematics · Allen Institute for AI

OLMo 2 7B on MATH-500: score, rank and what it means

OLMo 2 7B scores 49.0 on MATH-500, placing it #563 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
49.0
0–100 scale
Rank
#563
of 600
Percentile
6th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
47.7
points

Score distribution

The chart shows the top 10 models on MATH-500, with OLMo 2 7B 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 7B sits at #563 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 47.7 points. The median model in this index scores 76.0, which puts OLMo 2 7B below the midpoint.

Allen Institute for AI models average 60.7 on this benchmark. OLMo 2 7B is 11.7 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 7B is 4.7 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 49.0 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 $0.56 per million input tokens, OLMo 2 7B 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
Llama 3 Hyperbolic 1.5B Hyperbolic 32768 $0.45 48.4
Molmo 8B Allen Institute for AI 32768 $0.44 49.9
Yi-Lightning 1.5B 01.AI 4096 $0.54 50.0
Hunyuan-Large 1.5B Tencent 8192 $0.54 50.5
OLMo 2 7B Allen Institute for AI 16384 $0.56 51.7
Codestral 1.5B Mistral AI 8192 $0.52 49.9
DeepSeek-Coder 1.5B DeepSeek 16384 $0.58 51.0

Other benchmarks for OLMo 2 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 59.3 533 11th
GPQA Diamond 48.2 536 11th
SWE-bench Verified 35.5 552 8th
HumanEval 55.9 536 11th
AIME 2025 41.2 535 11th
LiveCodeBench 40.3 536 11th
IFEval 63.4 544 9th
TruthfulQA 59.1 540 10th
HellaSwag 67.0 564 6th
MMMU 50.1 553 8th
Arena Elo 1211.0 543 10th

FAQ

What score does OLMo 2 7B get on MATH-500?

OLMo 2 7B scores 49.0 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does OLMo 2 7B rank on MATH-500?

It ranks #563 of 600 models, in the 6th percentile. The leader is GPT-5.2 Max at 96.7.

Is OLMo 2 7B 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 7B cost?

OLMo 2 7B costs $0.56 per million input tokens and $2.58 per million output tokens.

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