A token counter is an essential tool for developers working with Large Language Models (LLMs) like GPT-3, GPT-4, BERT, and other AI systems. Tokens are the basic units that language models use to process text, and understanding token counts is crucial for:
API Cost Management: Most AI APIs charge based on token usage
Input Limit Compliance: Models have maximum token limits per request
Prompt Engineering: Optimize prompts to fit within token budgets
Text Analysis: Understand how different tokenizers process your content
Why Compare Different Tokenizers?
Different AI models use different tokenization methods. OpenAI's GPT models use tiktoken, while Hugging Face models may use various tokenizers. Our tool lets you compare how your text is tokenized across multiple systems, ensuring accuracy for your specific use case.
Supported Tokenizers
tiktoken (OpenAI): Used by GPT-3.5, GPT-4, and other OpenAI models
Transformers (Hugging Face): Supports BERT, RoBERTa, T5, and hundreds of models