A token is the basic unit that AI models use to process text. Roughly: 1 token ≈ 4 characters in English, or ≈ 0.75 words. In Chinese, each character is typically 1-2 tokens. Token count determines API costs.

How accurate is the token counting?

We use OpenAI's official tiktoken library for 99%+ accuracy when the exact tokenizer is available. For models without specific tokenizers, we use the closest approximation or estimation algorithm.

Why is token counting important?

Token count directly determines API costs and whether your request will succeed. Exceeding the context window causes errors. Accurate counting helps you budget and optimize your AI usage.

Tools

Count tokens for AI models

Input text

Tokens

Characters

Words

AI Token Calculator — Count Tokens for GPT, Claude & Gemini

Free AI token calculator. Count exact tokens using tiktoken for GPT-5.5, Claude, Gemini, DeepSeek and all major LLMs. Real-time token counting with character and word count. Perfect for developers estimating AI API usage.

Features

✓Count tokens with tiktoken precision (99%+ accuracy) for all major AI models
✓Real-time token counting as you type or paste text
✓Multi-language support: English, Chinese, Japanese, Korean, and mixed content
✓Copy and clear text functionality for easy workflow
✓Character and word count alongside token count

How to Use

1Paste or type your text in the input area. Tokens will be counted automatically using tiktoken for maximum accuracy.
2View the token count, character count, and word count in real-time.
3Use the Copy button to copy your text, or Clear to start over.
4The token count shows 'tiktoken exact' when using precise counting, otherwise it shows an estimate.

Frequently Asked Questions

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AI Model Database — Search, Compare & Explore AI Models

Comprehensive AI model database featuring leading models including GPT-5.5 Pro, Claude Opus 4.8, DeepSeek V4, Gemini 3.5 Flash. Real-time pricing synced regularly, advanced filtering by provider (OpenAI/Anthropic/Google/Meta and more), price tier (free models, budget/mid/premium), context window size, capabilities (Vision/Tools/Caching). Detailed specs: architecture, tokenizer, modalities, input/output pricing with cache discounts. Perfect for developers choosing AI models for production, PMs estimating API costs, and researchers comparing LLM specifications.