What are Tokens in AI?
Tokens are the "atoms" of Large Language Models. When you send text to an AI like GPT-4 or Claude, the model doesn't see words or characters. It sees a sequence of tokens—which can be a single character, a part of a word, or even an entire short word.
Why Accuracy Matters
Every AI model has a **Context Window** (e.g., 128k for GPT-4o, 200k for Claude 3). If your input exceeds this limit, the model will "forget" the beginning of the conversation. Additionally, API costs are calculated per token, making accurate estimation essential for budget management.
- GPT-4o / GPT-4: Use the `cl100k_base` tokenizer (supported by this tool).
- Claude & Gemini: While they use different tokenizers, `cl100k_base` provides a much closer estimation than standard word counting.
- Efficiency: On average, 1000 tokens is roughly equal to 750 words.
Tokenization Heuristics
English text tokenization is relatively predictable, but other languages and code are different:
- Languages: High-resource languages like English are very efficient (1 token per word). Low-resource languages may use 3-4 tokens per word.
- Code: Spaces and tabs are also tokens. Minifying code before sending it to an LLM can significantly reduce your token consumption.
- Special Characters: Emojis or rare symbols often count as multiple tokens (up to 4 per character).
Instruction: How to use
Paste your text into the main input area. Our tool uses a local implementation of the OpenAI tokenizer to count the tokens instantly. **Your text never leaves your device**, and no data is sent to OpenAI or any other server during this process.