Data story · provider

Allen Institute for AI: model lineup and pricing overview

Allen Institute for AI model lineup with prices, context windows and average benchmark scores. Nonprofit research institute behind OLMo and Molmo.

What the data shows

Allen Institute for AI has 14 models in the index. The average input price is $1.67 and the average output price is $7.05 per million tokens.

The strongest model by average score is olmo-2-instruct. The cheapest by input price is Molmo 1.5B.

How to read the lineup

  • Start with the best model for quality-sensitive work.
  • Use the cheapest model for high-volume tasks.
  • Check open-weight availability if self-hosting matters.
  • Keep a second provider for fallback.

Allen Institute for AI models

#ModelInput / 1MOutput / 1MContextAvg score
1OLMo 2 Instruct$3.03$14.4532,76871.7
2OLMo 2$2.99$11.5265,53671.0
3OLMo 2 Chat$2.94$12.0616,38470.6
4Molmo$2.49$9.4532,76868.5
5Molmo Instruct$2.53$9.2332,76868.3
6OLMo 2 Base$2.39$11.0565,53667.4
7Molmo Chat$2.40$10.8632,76866.7
8Molmo Base$2.02$7.534,09665.0
9OLMo 2 8B$0.64$3.184,09652.5
10OLMo 2 7B$0.56$2.5816,38451.7
11Molmo 8B$0.44$2.2932,76849.9
12Molmo 7B$0.42$2.2232,76849.3
13OLMo 2 1.5B$0.28$1.4116,38444.0
14Molmo 1.5B$0.21$0.938,19242.8

Methodology

This story uses the AI & LLM Index dataset: 600 models, 40 providers and 12 benchmarks. Prices are listed per million tokens. Scores are modelled estimates on a 0–100 scale and are not official benchmark results. Figures are rounded for readability.

Related

FAQ

What does the Allen Institute for AI: model lineup and pricing overview data show?

Allen Institute for AI model lineup with prices, context windows and average benchmark scores. Nonprofit research institute behind OLMo and Molmo.

Are the numbers official?

No. Prices and scores are compiled for this demo index. Benchmark values are modelled estimates, not official results. Verify figures with the provider or benchmark owner before making decisions.

How should I use this ranking?

Use it to form a shortlist. Check the specific model pages, compare price and context, and test the shortlist on your own examples before committing.