# LLM API Cost Calculator — GPT, Claude, Gemini

> Work out what a prompt costs per call, per day and per month, and compare the same workload across every major model.

This calculator prices a language-model workload from the token counts you actually send: input, output and cached input, multiplied by a request volume. It shows the cost per call and per period, splits input against output, and ranks every major model on the identical workload so the cheapest option for your particular input-to-output ratio is visible rather than guessed.

**URL:** https://convertto.tech/t/ai-api-cost-calculator
**Category:** AI & LLM Tools (https://convertto.tech/c/ai-tools)
**Privacy:** Runs entirely in the browser; no upload
**Cost:** Free, no sign-up
**Last updated:** 2026-08-01

## Key facts

- **Prices verified:** 2026-08-01
- **Models priced:** 25 across 7 providers
- **Privacy:** Runs entirely in your browser — nothing is uploaded
- **Cost:** Free, unlimited, no sign-up

## How to use

1. Choose the model.
2. Set the input tokens per request.
3. Set the output tokens per request.
4. Set the cached input tokens.
5. Set the requests.
6. Turn "Compare every model" on or off as needed.
7. Press Run, then download the result when it is ready.

## FAQ

### Why is output so much more expensive than input?

Input is processed in parallel in a single forward pass; output is generated one token at a time, each one requiring a full pass over the model. Output typically costs four to five times input, which is why a summarisation workload and a generation workload with the same total tokens can differ several-fold in price.

### What does prompt caching actually save?

Cached input is billed at roughly a tenth of the normal input rate, but writing to the cache costs about 1.25× a normal read. With a five-minute cache you break even on the second request; with a one-hour cache you need three. It only helps when a large prefix is genuinely identical between requests.

### Are reasoning tokens included?

They are billed as output even though they are not returned to you, so a reasoning model's real output count is higher than the visible response. Add your expected thinking tokens to the output figure to get a realistic number.

### How current are these prices?

Every figure carries the date it was checked — currently 2026-08-01 — and links to the provider's own price list. Treat this as a planning tool, not a quotation.

## Sources

- [Anthropic pricing](https://platform.claude.com/docs/en/pricing) — Anthropic
- [OpenAI pricing](https://openai.com/api/pricing/) — OpenAI
- [Gemini API pricing](https://ai.google.dev/gemini-api/docs/pricing) — Google

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