AI Token Calculator — Free Count Tokens for GPT, Claude
Count exact tokens using tiktoken for GPT, Claude, Gemini, DeepSeek, and all major LLMs. Real-time token counting with character and word count.
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
- ✓Cost estimation based on token count and model pricing — paste your text and see the API call cost instantly
- ✓Model-specific tokenizer switching — choose from GPT-4o, GPT-4, Claude 3.5, Gemini 1.5, and more
- ✓Context window monitoring — shows how much of the model's context window your text occupies
- ✓Batch mode — paste multiple prompts separated by a delimiter and see each prompt's token count separately
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.
- 5Select your AI model from the dropdown to use the correct tokenizer — GPT-4o, GPT-4, Claude 3 Sonnet, Claude 3 Haiku, Gemini 1.5 Pro, and more.
- 6Check the cost estimation panel at the bottom right to see how much an API call with this text would cost based on your selected model's input and output pricing.
- 7Monitor the context window usage bar — it shows how much of the model's maximum context window your text uses, helping you avoid context limit errors.
- 8Use batch mode: separate multiple prompts with '---' on its own line to count tokens for each prompt individually and see a running total.
- 9Plan your API calls: enter system prompt, few-shot examples, and user message separately to count the total tokens needed for a full request.
Frequently Asked Questions
What is a token?
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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?
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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?
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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.
How many tokens is my text? (English vs Chinese examples)
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English: 'Hello, how are you today?' = 6 tokens. 'The quick brown fox jumps over the lazy dog' = 10 tokens. Chinese: '今天天气真好' = 5 tokens. Chinese text typically costs 2-3x more tokens than equivalent English text because each character encodes more information.
How does token count affect API costs?
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Most AI providers charge per token, typically $0.01-0.15 per 1K input tokens and $0.03-0.60 per 1K output tokens depending on the model. A 2,000-token GPT-4 request costs around $0.06-0.12 total. The tool shows exact cost estimates based on the selected model's current pricing.
What is a context window and why does it matter?
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A context window is the maximum number of tokens a model can process in one request (input + output). GPT-4 has 8K or 32K variants, Claude 3 has 200K, Gemini 1.5 Pro has 1M. If your input exceeds the limit, the API returns an error. The tool's context bar shows your usage percentage.
Does token counting differ between models?
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Yes. Each model family has its own tokenizer with slightly different rules. GPT-4 uses cl100k_base, Claude uses SentencePiece, Gemini uses a custom tokenizer. The tool automatically selects the correct tokenizer when you pick a model. Using the wrong tokenizer can give inaccurate counts affecting cost calculations.
How to estimate tokens for a full API request with system prompt and conversation history?
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Count the tokens for the system prompt + each user message + each assistant response separately using batch mode, then sum them. Don't forget to add formatting overhead (~20 tokens per message boundary). The batch mode feature lets you paste all parts separated by '---' to see individual and total counts.
What happens when I exceed the context window?
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The API returns a 'context_length_exceeded' error. To fix this: (1) reduce your conversation history, (2) shorten the system prompt, (3) truncate the user input, (4) use a model with a larger context window (e.g., Claude 3 200K or Gemini 1.5 Pro 1M), or (5) implement sliding window summarization for long conversations.
Can I use this tool offline?
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Yes. The tokenizer and all calculations run entirely client-side. The tool uses a browser-compatible version of tiktoken that loads once. After the initial page load, you can disconnect from the internet and still count tokens accurately.