Data story · provider

Amazon: model lineup and pricing overview

Amazon model lineup with prices, context windows and average benchmark scores. Cloud provider behind the Nova model family.

What the data shows

Amazon has 14 models in the index. The average input price is $9.72 and the average output price is $43.75 per million tokens.

The strongest model by average score is nova-pro-max. The cheapest by input price is Nova Lite Nano.

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.

Amazon models

#ModelInput / 1MOutput / 1MContextAvg score
1Nova Pro Max$14.05$71.591,000,00081.2
2Nova Pro Pro$13.03$59.36200,00079.5
3Nova Pro$12.75$56.7132,76879.4
4Nova Pro Reasoning$13.48$65.09200,00079.4
5Nova Pro Turbo$13.18$51.70128,00078.4
6Nova Lite Reasoning$9.92$53.4232,76874.3
7Nova Lite Pro$9.69$46.58200,00074.1
8Nova Lite$9.20$41.9665,53673.4
9Nova Lite Max$9.79$35.24200,00073.4
10Nova Lite Turbo$9.14$42.638,19273.2
11Nova Pro Mini$7.74$31.2016,38470.6
12Nova Pro Nano$5.44$20.478,19265.4
13Nova Lite Mini$5.43$22.4816,38465.0
14Nova Lite Nano$3.29$14.038,19259.5

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 Amazon: model lineup and pricing overview data show?

Amazon model lineup with prices, context windows and average benchmark scores. Cloud provider behind the Nova model family.

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.