Budget planning guide
Monthly AI API Cost Calculator Guide
Monthly AI cost is not just price per million tokens. A realistic estimate includes input size, generated output, workflow repeats, traffic volume, retries, and the model mix used in production.
The monthly cost formula
Start with one successful user action. Estimate the input tokens sent to the model and the output tokens generated by the model. Then multiply that request by workflow rounds, runs per day, and 30 days.
A practical planning formula is: monthly cost equals input token cost plus output token cost, multiplied by workflow rounds, daily runs, and 30. Add retries and failed requests if users often revise prompts or if the workflow calls tools that can fail.
Example
A support workflow sends 4,000 input tokens and receives 900 output tokens. If each answer needs 2 model calls and the system handles 500 questions per day, monthly volume is about 120 million input tokens and 27 million output tokens before retries.
Inputs to collect before estimating
Use real samples when possible. Collect several typical prompts, retrieved document chunks, tool outputs, and final answers. Estimate the average and the high-end case separately so the budget covers ordinary usage and unusually large requests.
For file workflows, include extracted text rather than only the file size. For RAG workflows, count the chunks retrieved per question. For code analysis, exclude dependencies, generated files, lockfiles, and build artifacts unless the model truly needs them.
Do not ignore output tokens
Output can dominate the bill when the app writes long reports, JSON records, tables, rewritten documents, or code patches. If users only need a decision, ask for the decision and the evidence instead of a full narrative.
Use a safety buffer
Add a 10-30% buffer for chat history, longer-than-average documents, retries, tool errors, and model-specific tokenization differences. Use a larger buffer when the product has free-form prompts or accepts large uploads from users.
Measure after launch
Once the workflow is live, compare estimates with provider usage fields. Track input tokens, output tokens, cache hits, retries, failed requests, average cost per successful action, and the model used for each step. Replace estimates with observed values as soon as you have enough traffic.