Mathematics · Allen Institute for AI

OLMo 2 8B on MATH-500: score, rank and what it means

OLMo 2 8B scores 51.0 on MATH-500, placing it #548 of 600 models in the index. The benchmark average is 72.5 and the leader is GPT-5.2 Max at 96.7.

Score
51.0
0–100 scale
Rank
#548
of 600
Percentile
9th
within the index
Benchmark avg
72.5
all models
Leader
96.7
GPT-5.2 Max
Gap to leader
45.7
points

Score distribution

The chart shows the top 10 models on MATH-500, with OLMo 2 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, OLMo 2 8B sits at #548 of 600. The leader, GPT-5.2 Max, scores 96.7, so the gap to the top is 45.7 points. The median model in this index scores 76.0, which puts OLMo 2 8B below the midpoint.

Allen Institute for AI models average 60.7 on this benchmark. OLMo 2 8B is 9.7 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 8B is 2.7 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 51.0 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 $0.64 per million input tokens, OLMo 2 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
Phi-3.5 7B Microsoft 4096 $0.50 50.5
Mixtral 7B Mistral AI 16384 $0.70 54.1
Mixtral Groq 7B Groq 4096 $0.70 53.4
Llama 3 Replicate 1.5B Replicate 4096 $0.51 49.3
OLMo 2 8B Allen Institute for AI 4096 $0.64 52.5
QwQ 1.5B Alibaba Cloud 32768 $0.61 51.6
Mixtral Turbo 7B Together AI 8192 $0.68 53.2

Other benchmarks for OLMo 2 8B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 58.6 543 10th
GPQA Diamond 50.5 518 14th
SWE-bench Verified 39.4 527 12th
HumanEval 53.9 550 8th
AIME 2025 41.2 536 11th
LiveCodeBench 39.0 543 10th
IFEval 61.8 556 7th
TruthfulQA 60.0 530 12th
HellaSwag 71.3 515 14th
MMMU 50.3 550 8th
Arena Elo 1212.1 541 10th

FAQ

What score does OLMo 2 8B get on MATH-500?

OLMo 2 8B scores 51.0 on MATH-500 in this index. The benchmark average is 72.5 and the top score is 96.7.

How does OLMo 2 8B rank on MATH-500?

It ranks #548 of 600 models, in the 9th percentile. The leader is GPT-5.2 Max at 96.7.

Is OLMo 2 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 OLMo 2 8B cost?

OLMo 2 8B costs $0.64 per million input tokens and $3.18 per million output tokens.

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