Data story · provider

01.AI: model lineup and pricing overview

01.AI model lineup with prices, context windows and average benchmark scores. AI startup founded by Kai-Fu Lee, maker of Yi.

What the data shows

01.AI has 14 models in the index. The average input price is $2.39 and the average output price is $10.97 per million tokens.

The strongest model by average score is yi-lightning. The cheapest by input price is Yi-Large 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.

01.AI models

#ModelInput / 1MOutput / 1MContextAvg score
1Yi-Lightning$4.22$23.0732,76877.2
2Yi-Lightning Instruct$4.16$22.74128,00076.5
3Yi-Lightning Chat$3.79$19.1432,76875.5
4Yi-Large$3.40$13.3532,76873.5
5Yi-Large Chat$3.49$13.9765,53673.5
6Yi-Large Instruct$3.48$13.4632,76873.4
7Yi-Lightning Base$3.31$16.3116,38472.7
8Yi-Large Base$2.78$10.8416,38470.3
9Yi-Lightning 8B$1.16$5.134,09659.2
10Yi-Large 8B$0.88$3.9832,76856.1
11Yi-Lightning 7B$1.00$3.6932,76855.9
12Yi-Large 7B$0.83$3.254,09655.0
13Yi-Lightning 1.5B$0.54$2.524,09650.0
14Yi-Large 1.5B$0.42$2.138,19246.8

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 01.AI: model lineup and pricing overview data show?

01.AI model lineup with prices, context windows and average benchmark scores. AI startup founded by Kai-Fu Lee, maker of Yi.

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.