AI Token Cost Calculator

AI Token Cost Calculator is designed to estimate AI prompt size, cached input, context fit, and provider cost before sending one request or a repeated workload.

Input: prompt text or a local text file, workload preset, provider and model, expected output tokens, cached percentage, usage period, and request count. Output: tokenizer or estimated input count, total tokens, context status, cached and uncached cost breakdown, per-request cost, period cost, and optional model comparison.

OpenAI text uses a browser-loaded o200k tokenizer while other providers use a labeled character estimate; listed per-million input, cache, and output rates are then applied to the selected request volume.

Check the tokenizer status, context warning, pricing verification date, and provider source; use custom rates when the official or negotiated price differs.

Use it when you are checking whether a long RAG context or coding-agent turn fits the context window and what a daily or monthly run will cost.

The workflow is intended for AI builders, prompt engineers, marketers, documentation teams, and product owners.

Provider message framing can add tokens, non-OpenAI counts are estimates, and model pricing or context limits can change after the displayed verification date.

A common mistake is ignoring cached input and multiplying only one request when planning an agent, batch, or monthly workflow.

Prompt text and selected local files are measured in the browser and no AI API call is made.

For a broader workflow, use the word counter or Markdown editor to inspect and trim source material before estimating, then compare models with the same workload assumptions.

If the result matters later, copy the estimate with the model, prompt version, request count, cache assumption, and pricing verification date when planning repeated jobs.