Code Flux

Token Counter

Estimate how many tokens your text contains for LLM API usage and cost calculation.

0
Estimated Tokens
$0.000000
Input Cost
$0.000000
Output Cost (same length)

Text Statistics

Characters:0
Words:0
Lines:1
Chars/Token:0

* Token counts are estimates based on common tokenization patterns. Actual counts may vary depending on the specific tokenizer used by each model. Pricing shown is per 1K tokens based on publicly available rates.

What is Token Counter?

A Token Counter estimates the number of tokens in your text for use with Large Language Model (LLM) APIs like OpenAI's GPT-4 or Anthropic's Claude. Tokens are the basic units that LLMs process - they can be words, parts of words, or punctuation. Understanding token counts helps you manage API costs and stay within context window limits. This tool provides estimates based on common tokenization patterns.

How to Use

  1. Paste or type your text into the input area
  2. View the estimated token count in real-time
  3. Select a model to see estimated API costs
  4. Use this information to optimize your prompts and manage costs

Common Use Cases

  • Estimating OpenAI API costs before making requests
  • Checking if prompts fit within context window limits
  • Optimizing prompt length for cost efficiency
  • Comparing different models based on pricing
  • Planning token budgets for AI applications

Frequently Asked Questions

The estimate is approximately 90-95% accurate for most text. It uses a character-based approximation (roughly 4 characters per token) which works well for English text. Actual token counts may vary slightly depending on the specific tokenizer used by each model.
Input tokens are what you send to the API (your prompt), and output tokens are what the model generates in response. Most APIs charge different rates for each, with output tokens typically costing more.
More capable models (like GPT-4) require more computational resources, making them more expensive. Smaller models (like GPT-3.5 Turbo) are faster and cheaper but may be less capable for complex tasks.
The context window is the maximum number of tokens a model can process in a single request (input + output combined). For example, GPT-4 Turbo has a 128K token context window, while GPT-3.5 Turbo has 16K.
Yes! As you type, the tool instantly updates token counts and cost estimates. This helps you optimize your prompts before sending them to the API.

Privacy Guarantee

We process all data directly in your browser. Nothing is sent to our servers. Your data stays on your device, ensuring complete privacy and security. Feel free to use this tool with sensitive information.