Prompt Token Estimator
Estimate token usage, count characters/words, and calculate cost matrices for your LLM prompts.
How Text Tokenization Impacts API Budgets
Unlike standard text processors that count words, Large Language Models break down characters into numerical chunks called tokens. A token can represent a single character, a sub-word unit, or an entire word. In general, 100 tokens represent roughly 75 English words.
Because LLM providers charge based on token volumes, optimizing prompt sizes is essential for managing product budgets. Our estimator helps developers inspect character sizes, analyze metrics, and compare pricing options dynamically.
Frequently Asked Questions
How does this tool estimate tokens?
English text typically averages 4 characters per token or 0.75 words per token. The tool analyzes your text length and uses customizable character ratio ranges to output estimated token figures.
Is the pricing estimate accurate?
It is an approximation based on standard input token rates (per 1,000,000 tokens) for common models like GPT-4o and Claude 3.5 Sonnet. Actual pricing may vary slightly based on provider updates.
Why is tracking token usage important?
Orchestrating large context windows can quickly become expensive. Estimating input sizes beforehand allows developers to benchmark costs and prevent payload truncation errors.