AI API Budget Calculator
Plan your monthly AI API budget based on usage volume, model selection, and request patterns.
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How to use this calculator
Effective requests account for cache hits, which reduce the number of real API calls. The formula computes input and output token costs separately, then scales daily costs to monthly and annual projections.
- 1
Enter your expected number of API requests per day and the average input and output token counts per request.
- 2
Enter the input and output pricing from your model provider's pricing page (in dollars per million tokens).
- 3
Optionally set a cache hit rate if you use prompt caching — the calculator will show your monthly savings.
Frequently asked questions
What is prompt caching and how does it reduce costs?
Prompt caching stores the computed key-value states of a prompt prefix. When a later request reuses the same prefix, the provider serves the cached result at a lower price or for free. Anthropic's Claude, for example, charges 10% of normal input price for cache hits. Set your cache hit rate to see the budget impact.
How do I estimate average input and output token counts?
Run a sample of 50–100 real requests through your system and log the token counts from the API response. Average them. Most providers include prompt_tokens and completion_tokens in every API response, making this straightforward to instrument.
Is the 30-day month estimate accurate enough for budgeting?
For billing purposes, most providers charge based on actual calendar months (28–31 days). Using 30 days gives a close approximation. For annual budgets, the 365-day figure is accurate to within one or two billing cycles.
AI API Budget Calculator — Monthly Cost Planning for LLM Applications
Why you need an AI budget calculator
AI API costs are variable — they scale directly with usage, token length, and model choice. Without a budget model, teams are frequently surprised by month-end bills. This calculator lets you set input variables (requests/day, token counts, pricing) and immediately see daily, monthly, and annual projections so you can make informed architecture decisions.
Caching strategies that cut AI costs dramatically
Prompt caching is one of the highest-leverage cost reduction techniques available. Applications with repetitive system prompts (e.g., a fixed 2,000-token system message sent with every request) can cache that prefix and pay as little as 10% of the normal input price on cache hits. At 70% cache hit rate on 5,000 daily requests, monthly savings can reach thousands of dollars.
Learn more from an authoritative source:
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Results are estimates for informational purposes only and do not constitute professional financial, medical, legal, or technical advice. Read full disclaimer →