Knowledge · Allen Institute for AI

OLMo 2 Base on MMLU-Pro: score, rank and what it means

OLMo 2 Base scores 69.8 on MMLU-Pro, placing it #398 of 600 models in the index. The benchmark average is 73.5 and the leader is GPT-5.2 Pro at 91.6.

Score
69.8
0–100 scale
Rank
#398
of 600
Percentile
34th
within the index
Benchmark avg
73.5
all models
Leader
91.6
GPT-5.2 Pro
Gap to leader
21.8
points

Score distribution

The chart shows the top 10 models on MMLU-Pro, with OLMo 2 Base highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 91.6
GPT-5.1 Max 91.3
Claude Opus 4.5 Pro 91.2
Claude Opus 4.5 Reasoning 90.7
Gemini 3 Pro Reasoning 90.1
GPT-5.1 Reasoning 90.0
GPT-5.2 89.9
Claude Opus 4.5 Max 89.5
GPT-5.2 Vision 89.5
Gemini 3 Pro Max 89.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
3 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
4 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
5 Gemini 3 Pro Reasoning Google DeepMind 200000 $19.69 87.5
6 GPT-5.1 Reasoning OpenAI 400000 $20.27 88.3
7 GPT-5.2 OpenAI 2000000 $19.71 88.0
8 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
9 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On MMLU-Pro, OLMo 2 Base sits at #398 of 600. The leader, GPT-5.2 Pro, scores 91.6, so the gap to the top is 21.8 points. The median model in this index scores 76.1, which puts OLMo 2 Base below the midpoint.

Allen Institute for AI models average 65.6 on this benchmark. OLMo 2 Base is 4.2 points above that provider line, so it is a stronger result than the average Allen Institute for AI model.

Among open-weight models, the average is 72.1. OLMo 2 Base is 2.3 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 69.8 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 $2.39 per million input tokens, OLMo 2 Base is below the median input price of $4.00 across the 600 models scored on MMLU-Pro. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Doubao 1.5 Pro Nano ByteDance 16384 $5.78 66.6
Embed 4 Reasoning Cohere 4096 $5.50 65.3
StableLM 2 Instruct Stability AI 16384 $1.93 65.2
Command A Nano Cohere 8192 $5.90 66.3
OLMo 2 Base Allen Institute for AI 65536 $2.39 67.4
ERNIE 4.5 Nano Baidu 32768 $6.01 65.6
Llama 4 Maverick 8B Meta AI 4096 $1.64 63.4

Other benchmarks for OLMo 2 Base

BenchmarkScoreRankPercentileRelative
GPQA Diamond 62.1 390 35th
SWE-bench Verified 52.0 406 32th
HumanEval 70.2 391 35th
MATH-500 72.6 362 40th
AIME 2025 62.4 373 38th
LiveCodeBench 58.1 389 35th
IFEval 76.4 383 36th
TruthfulQA 72.5 376 37th
HellaSwag 81.5 359 40th
MMMU 64.1 388 35th
Arena Elo 1326.6 391 35th

FAQ

What score does OLMo 2 Base get on MMLU-Pro?

OLMo 2 Base scores 69.8 on MMLU-Pro in this index. The benchmark average is 73.5 and the top score is 91.6.

How does OLMo 2 Base rank on MMLU-Pro?

It ranks #398 of 600 models, in the 34th percentile. The leader is GPT-5.2 Pro at 91.6.

Is OLMo 2 Base good at MMLU-Pro?

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 MMLU-Pro score calculated?

MMLU-Pro is a knowledge 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 Base cost?

OLMo 2 Base costs $2.39 per million input tokens and $11.05 per million output tokens.

Related