Estimate AI API cost from usage, not the length of the visible answer
Separate input, cached input, output and tool charges, use current rates and include retries in a realistic workload estimate.
In brief
An AI request can be billed for more than the visible answer. Count the provider’s reported input and output units, then add applicable cached-input, tool, storage, image or audio charges.
A small representative workload gives a better estimate than multiplying one unusually short answer by a hoped-for user count.
Use the correct arithmetic
For token rates quoted per million, divide the billable token count by one million before multiplying by the rate. When total input includes cached tokens, split it into uncached and cached portions. Add tools or storage separately under their own documented units.
Include the full workflow
Retrieval, multiple model calls and a retry can all belong to one user task. Voice and image paths may use different units or conversions. Track cost per completed useful task as well as cost per API request, and account for failed tasks rather than erasing them from the estimate.
Bound the forecast
Estimate a typical case and a heavier case using observed lengths and allowed usage. Keep dated rate references and review after model or workflow changes. Use application limits and monitoring; a budget notification alone may arrive after spending has occurred.
Before you act
Rates and billing units differ by model and modality. Usage estimates are not guarantees, and a chat subscription does not automatically pay for API calls.
What to do next
- Read current pricing for the exact model, endpoint and modality.
- Measure representative requests without retaining sensitive content.
- Calculate normal and high-usage cases including retries, tools and fixed or storage costs.
