Multimodal · Allen Institute for AI

OLMo 2 1.5B on MMMU: score, rank and what it means

OLMo 2 1.5B scores 46.4 on MMMU, placing it #577 of 600 models in the index. The benchmark average is 67.1 and the leader is GPT-5.2 Max at 86.9.

Score
46.4
0–100 scale
Rank
#577
of 600
Percentile
4th
within the index
Benchmark avg
67.1
all models
Leader
86.9
GPT-5.2 Max
Gap to leader
40.5
points

Score distribution

The chart shows the top 10 models on MMMU, with OLMo 2 1.5B highlighted. Longer bars mean higher scores.

GPT-5.2 Max 86.9
GPT-5.1 Reasoning 86.2
GPT-5.2 85.3
Claude Sonnet 4.5 Reasoning 85.2
GPT-5.1 Max 85.1
Grok 4 Pro 84.9
Claude Opus 4.5 Reasoning 84.6
Claude Sonnet 4.5 Pro 84.5
GPT-5.2 Pro 84.4
GPT-5.2 Vision 84.4

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-5.2 OpenAI 2000000 $19.71 88.0
4 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
5 GPT-5.1 Max OpenAI 2000000 $20.50 87.9
6 Grok 4 Pro xAI 1000000 $19.00 85.4
7 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2
8 Claude Sonnet 4.5 Pro Anthropic 1000000 $18.73 86.7
9 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
10 GPT-5.2 Vision OpenAI 1000000 $19.03 87.4

What this score means

On MMMU, OLMo 2 1.5B sits at #577 of 600. The leader, GPT-5.2 Max, scores 86.9, so the gap to the top is 40.5 points. The median model in this index scores 70.0, which puts OLMo 2 1.5B below the midpoint.

Allen Institute for AI models average 58.5 on this benchmark. OLMo 2 1.5B is 12.1 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 52.4. OLMo 2 1.5B is 6.0 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 46.4 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 MMMU. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Mixtral Groq 1.5B Groq 4096 $0.34 46.1
Llama 3 Novita 1.5B Novita AI 4096 $0.41 49.1
Nemotron Nano 7B NVIDIA 8192 $0.35 47.5
Llama 3 DeepInfra 1.5B DeepInfra 32768 $0.48 48.8
OLMo 2 1.5B Allen Institute for AI 16384 $0.28 44.0
Embed 4 Nano Cohere 8192 $1.48 49.7
Nemotron Nano 8B NVIDIA 8192 $0.46 48.1

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
MATH-500 41.9 591 2th
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
Arena Elo 1142.8 586 2th

FAQ

What score does OLMo 2 1.5B get on MMMU?

OLMo 2 1.5B scores 46.4 on MMMU in this index. The benchmark average is 67.1 and the top score is 86.9.

How does OLMo 2 1.5B rank on MMMU?

It ranks #577 of 600 models, in the 4th percentile. The leader is GPT-5.2 Max at 86.9.

Is OLMo 2 1.5B good at MMMU?

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 MMMU score calculated?

MMMU is a multimodal 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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