Queendom Tools

LLM API Token Cost Calculator

Calculate your LLM API spend instantly. AI model pricing splits input vs output tokens per 1M, often at a 3-5x ratio; enter current rates to get accurate costs.

Total Estimated Cost

$0.00
Input Cost: $0.00
Output Cost: $0.00
Cost per Request: $0.00

Understand Your LLM API Spend

For AI developers and indie hackers building LLM apps, this tool eliminates guesswork by modeling API budget against dynamic token pricing—where output tokens often cost 3-5× more than inputs—and allows pasting fresh vendor rates so you never overestimate spend based on outdated lists.

Accurately projecting costs is crucial for sustainable development. This calculator provides a transparent way to see how varying token volumes and per-million rates impact your overall budget, keeping you agile as provider prices shift.

How to Use This Calculator

  1. Enter your average Input Tokens and Output Tokens per API call.
  2. Specify how many requests you expect (set Requests > 1 for bulk estimates).
  3. Type your API provider's current Input and Output rates in $/1M tokens.
  4. View the live Total Cost, plus breakdowns showing how much each part contributes.

FAQ

Q: How to estimate monthly LLM API costs based on projected traffic?

A: Multiply your average input/output tokens per query by daily request volume, apply the per-million rates to get daily spend, and multiply by 30 for a monthly projection while accounting for traffic variance.

Q: Why is my output token cost higher than input in most LLM APIs?

A: Vendors typically price outputs 3–5× higher than inputs because text generation requires significantly more inference compute steps than processing the prompt to produce a completion.

Q: Are LLM API token prices fixed permanently by the provider?

A: No; major providers like OpenAI, Anthropic, and Google frequently adjust prices—sometimes cutting them by half—so always use a calculator that accepts manual rate entry rather than relying on cached price tables.

Q: How can I reduce LLM API costs without switching models?

A: Shorten system prompts to reduce input tokens, enforce concise response formats to lower output tokens, implement caching for repeated queries, and batch requests where possible to minimize per-request overhead.