Words are human units
Words are useful for reading and writing, but they are not the unit most AI APIs use for billing.
Tokens vs words
Tokens vs Words
Words are easy for humans to count, but AI models usually process text as tokens. Paste your text to compare characters, words, estimated tokens, and potential cost.
Tokens are model units
A token can be a word, part of a word, punctuation, whitespace, code, or formatting.
Counts vary by text
Language, punctuation, code, markdown, JSON, and message structure can all change token estimates.
Cost usually follows tokens
AI cost is usually based on input and output tokens, not word count. PromptMeter estimates all three side by side.
Calculator
Estimate your AI prompt cost
Paste a prompt, choose an example pricing profile, and estimate cost per prompt run, per day, and per month.
Input tokens are what you send to the AI model. Output tokens are what the model returns. API providers often price them separately.
Advanced settings
Prices are manual for now. Example: if your provider charges $2 input and $10 output per 1M tokens, enter 2 and 10.
Energy usage is a rough estimate. Actual energy depends on model, hardware, provider, datacenter efficiency, workload, and region.
FAQ
Tokens vs words FAQ
Is one word the same as one token?
No. Some words are one token, some split into multiple tokens, and punctuation or formatting can count too.
Why do tokens matter for AI cost?
Providers often price API usage by tokens. More input or output tokens usually means higher cost.
Can token counts vary by model?
Yes. Different models and tokenizers can count the same text differently, so these estimates stay approximate.