AI Token Analyzer & Context Visualizer
Estimate token counts, visualize context usage, and optimize your prompts for any LLM.
Stop guessing your token counts. Our advanced analyzer estimates usage for models like GPT-4 and Claude, visualizes how much context you are using, and helps you optimize your prompts for lower costs and better performance. The essential tool for serious AI developers.
Token Counter Tool
Paste your text below to get an estimated token count for GPT-style models.
Estimated Token Count
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Characters
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Words
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Sentences
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Advanced Configuration
Note: This is an estimate. The exact token count can vary based on the specific tokenizer used by the model (e.g., OpenAI's `tiktoken`).
About This Tool
The AI Token Analyzer & Context Visualizer is a professional-grade utility for anyone building with large language models. A "token" is the fundamental unit of text an LLM processes, and understanding tokenization is critical for managing costs and performance. This tool goes beyond simple counting. It provides a robust, heuristic-based estimate of token count and enhances it with powerful configuration options. By adjusting the "Characters per Token" and "Words per Token" sliders, you can simulate how different tokenizers might behave and fine-tune the estimate for your specific use case. It's an indispensable utility for prompt engineers, AI developers, and content creators who need to optimize their inputs for both cost and performance, ensuring prompts fit within a model's context window and are as efficient as possible.
How to Use This Tool
- Paste your desired text, prompt, or code snippet into the large text area.
- The tool will instantly analyze the input and display the estimated token count, character count, word count, and sentence count.
- Use the "Advanced Configuration" sliders to adjust the tokenization heuristic to better match the model you are using.
- Observe how changes in the configuration affect the final token count.
- Use the "Reset" button to clear the text area and all configurations to start over.
In-Depth Guide
What Exactly is a Token?
Think of tokens as pieces of words. For common English words, one word is often one token. For example, "cat" is one token. However, less common words get broken down. "Tokenization" becomes three tokens: "token", "iz", "ation". This allows the model to handle any word, even ones it has never seen. Punctuation and spacing also count, making token counting less than straightforward.
Why is Token Counting So Important?
There are two primary reasons: cost and context. First, every major AI provider (OpenAI, Google, Anthropic) bills you based on the number of tokens you send (input) and receive (output). Managing tokens is managing your budget. Second, every model has a "context window," which is the maximum number of tokens it can remember at one time. For example, GPT-4 has variants with 8,000 to 128,000 token windows. If your prompt and the expected response exceed this limit, the model will fail or forget earlier parts of the conversation.
How This Estimator Works & Advanced Configuration
The only way to get a 100% accurate count is to use the official tokenizer for a specific model. However, for a quick and reliable web-based tool, we use a proven heuristic based on characters and words. This tool enhances that by giving you control. The default settings (4 chars/token, 0.75 words/token) are a good general approximation. However, you can adjust them. If you are working with a model that is very efficient, you might increase the values. If you are working with code or a complex language, you might decrease them to reflect a higher token density. This allows you to build an intuitive sense of how tokenization works.
Optimizing Your Prompts
Prompt optimization is both an art and a science. Use this tool as your workbench. Try rephrasing a sentence and see if the token count drops. Replace a paragraph with a more concise bulleted list. Remove conversational filler. By seeing the token count change in real-time, you can develop the skills to create prompts that are not only effective but also highly efficient, saving you money and improving response times.