AI API Cost Calculator (LLM Token Pricing)
Estimate what an LLM-powered feature will cost — tokens per request, requests per month, input/output prices per million tokens, prompt caching and batch discounts. Works for any model: enter your provider's current prices.
Results are estimates for planning; real-world values vary.
How to use
- 1Enter the average input (prompt) and output (response) size of one request — in tokens, or words if you don't know the token count.
- 2Enter how many requests you expect per month.
- 3Copy the model's input and output prices per million tokens from your provider's pricing page.
- 4Add the share of input served from the prompt cache and any batch discount if you use them.
How it's calculated
Cost per request = (uncached input × input price + cached input × cache price + output × output price) ÷ 1,000,000, then × (1 − batch discount). Words are converted at about 1.33 tokens per English word.
Frequently asked questions
How many tokens is a word?
For English text, roughly 3/4 of a word per token — 100 words ≈ 133 tokens. Code, non-English text and numbers use more tokens per word. Your provider's tokenizer gives the exact count.
Why is output more expensive than input?
Output tokens are generated one at a time, which takes much more compute than reading the prompt. Output prices are typically 3–5× the input price.
What is prompt caching?
If many requests share a long identical prefix (system prompt, documents, examples), providers can cache it and bill those tokens at a steep discount — often 90% off the normal input price.
Where do I find current prices?
On your AI provider's pricing page. Prices change often and differ per model, so this calculator lets you enter them rather than relying on a built-in list that could go stale.