LLM Token Counter
Count tokens for any AI model instantly. 100% private — everything stays in your browser.
Estimated count — actual tokenization may vary slightly by model
Compare Model Tokenization
| Model | Estimated Tokens | Context Window | Usage |
|---|
What Are Tokens?
Tokens are how AI models like GPT-4o, Claude, and Gemini read text. Instead of reading character by character, they split text into small pieces called tokens. A token can be as short as one character (like "a" or "!") or as long as a whole word (like "apple" or "because"). On average, 1 token ≈ 4 characters of English text, or about ¾ of a word.
For example, the sentence "AI is transforming how we work" might be split into tokens like: ["AI", " is", " transforming", " how", " we", " work"] — about 6 tokens for a 5-word sentence.
Why Token Counting Matters
- Context Windows: Every AI model has a maximum number of tokens it can handle at once (e.g., 128K for GPT-4o, 200K for Claude). Going over means your text gets truncated.
- API Costs: Most AI providers charge per token — both for input (what you send) and output (what the model generates).
- Prompt Optimization: Shorter prompts = fewer tokens = lower costs + faster responses.
100% Private & Secure
This token counter runs entirely in your browser. No text is ever sent to any server. Your prompts, code, and documents never leave your device. This makes it safe for sensitive content like private documents, proprietary code, or personal information.
Frequently Asked Questions
A token is a unit of text that AI models process. Tokens can be words, parts of words, or individual characters. For example, "hello" is 1 token, while "unbelievable" might be split into 3 tokens: "un", "believ", "able". Different models use different tokenization methods, which is why the same text can have different token counts across models.
This tool provides an estimation based on proven approximation algorithms. While actual tokenization varies by model, our estimation is typically within 5-10% accuracy for English text. For production use where exact counts matter, we recommend using the official tokenizer for your specific model (e.g., tiktoken for OpenAI models).
No, never. All token counting is done locally in your browser using JavaScript. Your text never touches any server, API, or external service. You can even use this tool offline after the page loads. Your privacy is guaranteed.
Each AI model family uses its own tokenization method (encoding). OpenAI uses tiktoken with different encodings (cl100k_base, o200k_base), Claude uses its own tokenizer, Gemini uses SentencePiece, and so on. This means the same text may be split into different numbers of tokens across models. Our tool adjusts its estimation per model for better accuracy.
Token pricing varies by model and provider. As a rough guide: GPT-4o costs ~$2.50 per 1M input tokens, Claude 3.5 Sonnet costs ~$3.00 per 1M input tokens, and Gemini 1.5 Flash costs as little as $0.075 per 1M input tokens. Output tokens are typically 3-5x more expensive than input tokens. Our tool calculates real-time cost estimates based on current published pricing.
A context window is the maximum number of tokens an AI model can process in a single request. Think of it as the model's "working memory." For example, GPT-4o has a 128K token context window, Claude 3.5 Sonnet has 200K, and Gemini 1.5 Pro has 1M tokens. If your input exceeds the context window, older parts get dropped. Our tool shows you what percentage of the context window your text uses.