Token Counter

Estimate token counts for GPT-4, Claude, Gemini, and Llama models. See context window usage and cost estimates.

What is Token Counting?

Token counting is the process of estimating how many tokens a piece of text will consume when processed by an AI language model. Tokens are the fundamental units that models like GPT-4, Claude, Gemini, and Llama use to process text — roughly 3-4 characters or about 0.75 words in English. Token counts determine both the cost of API calls and whether your text fits within a model's context window.

This tool estimates token counts for multiple AI models, shows context window usage, and calculates estimated API costs based on current pricing.

How to Use This Token Counter

Paste your text — Enter the text you want to count tokens for in the input area.

Select a model — Choose from GPT-4, Claude, Gemini, Llama, or other popular models.

View the count — See the estimated token count, character count, and word count instantly.

Check context usage — A visual indicator shows how much of the model's context window your text consumes.

See cost estimates — View estimated API costs for processing your text as input or output tokens.

Common Use Cases

Cost estimation — Estimate API costs before sending large prompts to paid AI model APIs.

Prompt engineering — Check that your prompts and system messages fit within the model's context window.

Chunking text — Determine how to split large documents into chunks that fit within token limits for RAG pipelines.

Model comparison — Compare token counts and costs across different AI providers to choose the most cost-effective option.

Frequently Asked Questions

What is a token in AI models?

A token is a piece of text that AI models process — roughly 3-4 characters or about 0.75 words in English. Models like GPT-4 and Claude use tokenizers to break text into these units. Token counts determine API costs and context window limits.

How accurate is this token counter?

This tool provides estimates using a characters-per-token heuristic (~3.5-4 chars/token). Actual token counts vary by model tokenizer. For exact counts, use the provider's official tokenizer (e.g., OpenAI's tiktoken). Estimates are typically within 10-15% of actual counts for English text.

What is a context window?

The context window is the maximum number of tokens a model can process in a single request, including both input and output. For example, GPT-4o has a 128K context window, while Claude Sonnet 4 has 200K. Going over the limit means the model can't process your full input.