AI API Cost
OpenAI API Cost Calculator: How to Estimate Monthly AI Spend
A practical guide to forecasting OpenAI API spend from tokens, requests per day, active users, and model pricing.
6 min read - Published 2026-06-16 - Updated 2026-06-16
Start with real request shape
A useful AI cost forecast starts with a realistic request, not a guess. Include the system prompt, user message, retrieved context, tool definitions, and the expected assistant response length.
For a production chatbot, the same feature can have very different costs depending on whether you send only the latest user message or the full conversation history with documents.
Separate input and output tokens
Most AI providers price input tokens and output tokens differently. Output tokens are often more expensive because the model has to generate them step by step.
A simple monthly forecast is: cost per request multiplied by requests per day, then multiplied by 30. For SaaS planning, repeat the same calculation for 100, 1,000, and 10,000 active users.
Use cheaper models for routine paths
Do not send every workflow to the most expensive model. Classifiers, short summaries, routing, and formatting jobs can usually run on small or fast models.
Reserve frontier reasoning models for the moments where accuracy, complex planning, or coding quality changes the user outcome.
Estimate your own AI API cost.
Use the calculator with your model, token counts, and request volume.