How much does an AI product-recommendation feature cost?
Figuring out how to estimate an AI recommendation feature's cost is one of the first budgeting questions AI teams hit. Built for e-commerce and marketplace teams, this tool skips the generic rate card and gives you a working estimate you can tune to your traffic. The result reacts live as you adjust the inputs.
Results update automatically as you type.
- Input cost
- $0.00250
- Output cost
- $0.00500
- Per request
- $0.00750
- Per day
- $7.50
- Per month
- $225.00
Why this isn't trivial
The part people underestimate: recommendations often pass catalog and user context into each call, so input tokens grow with catalog size. In practice the biggest savings come from pre-filtering candidates before the LLM and caching per-user results, so it is worth modelling before you commit.
How it's calculated
We estimate this by estimating context tokens per recommendation request and applying model rates across request volume. Every figure uses the current provider prices baked into the site (reviewed daily), and you can override any input to match your own assumptions.
Frequently asked questions
Should the LLM see the whole catalog?+
No — pre-rank with cheap methods and let the LLM refine a short list to control input cost.
Can I cache recommendations?+
Yes — caching per-user or per-segment results avoids repeat LLM calls.
Are these prices up to date?+
Yes. The model prices behind this calculator are refreshed and reviewed daily, so your estimate reflects current provider rates rather than a stale snapshot.
Related
Estimates for planning. Pricing data last reviewed 28 July 2026.