Free tools / Cost calculator
AI agent cost calculator.
Estimate what an agent or LLM workflow costs to run each month, and compare it with doing the work by hand. Every number is an assumption you can change.
1 · The workflow
2 · Model usage per task
Prices are example tiers. Check your provider's current list prices; cached input is counted at ~10% of the input price.
3 · People and overhead
How the estimate works
Four numbers decide most of the bill.
- → model cost = (input tokens × input price, less cached input) + (output tokens × output price), per call
- → per task = model cost × calls per task; per month = per task × tasks
- → review = share of tasks a person checks × minutes per check × hourly cost
- → running cost = model + review + hosting and monitoring; compared with minutes by hand × hourly cost
FAQ
Questions about agent costs
What drives the cost of an AI agent?
Tokens per model call, the number of calls per task and the monthly volume, plus the time people spend reviewing output and the hosting and monitoring around it. Long context and retries are the usual surprises.
How does prompt caching lower the cost?
Input that repeats across calls, such as instructions, tool definitions and reference documents, can be read from a cache at a fraction of the normal input price on providers that support it. The calculator counts cached input at about 10% of the input price.
Should we use the largest model?
Use the smallest model that passes your evaluation set, and route only the hard cases to a larger one. Model choice is often the biggest lever on the monthly bill.
What does the estimate leave out?
The one-off build: integrations, the evaluation set, the quality gate and handover. We quote that after a scoping sprint, once the workflow and its data are clear.
Book an AI scoping call
Bring one workflow. We'll tell you if an agent should run it.
or write to contact@byteandrise.com · we work under NDA