Count words, tokens, and characters in your AI prompts for ChatGPT, Midjourney, and Claude.
An AI prompt word counter is a specialized text analysis tool designed to help writers, developers, and content creators measure the length of their prompts before submitting them to AI models like ChatGPT, Claude, Gemini, and Midjourney. Unlike a basic word counter, it also estimates token count — the unit that large language models actually use to process text.
Understanding token count is essential because AI models have strict context window limits. A prompt that seems short in words can consume far more tokens than expected, especially when it contains code snippets, special characters, or non-English text. This tool gives you an instant breakdown so you can optimize your prompts for maximum effectiveness within each model's limits.
This tool analyzes your text in real-time as you type or paste it. Here's what each metric means:
Model Token Limits Reference: ChatGPT-4o supports up to 128K tokens, Claude 3.5 Sonnet up to 200K tokens, Gemini 1.5 Pro up to 1M tokens, and Midjourney enforces approximately 4,000 characters per prompt. Llama 3 models range from 8K to 128K depending on the variant.
Use this tool to ensure your prompts fit comfortably within your target model's context window, leaving room for the model's response.
A token is the basic unit that AI models use to process text. In English, one token typically corresponds to about ¾ of a word, or roughly 4 characters. However, common words like "apple" may be a single token, while less common words or typos may be split into multiple tokens. Non-English text, code, and special characters often consume more tokens per word than plain English.
Several factors increase token consumption: code blocks and special characters are tokenized less efficiently than plain text, repeated phrases still consume tokens each time, and whitespace and formatting characters are counted. If your prompt includes system instructions, few-shot examples, or long context passages, the token count can grow quickly even if the word count seems moderate.
The estimation uses a rough ratio of 1 token per 4 characters, which works well for English text in most transformer-based models. However, each model uses a different tokenizer — GPT models use tiktoken, Claude uses its own BPE tokenizer, and Gemini uses SentencePiece. For exact token counts, you would need to use the specific model's tokenizer library. This tool provides a reliable approximation for quick reference.
Yes. Midjourney enforces a character limit (approximately 4,000 characters) rather than a token limit. The character count shown by this tool tells you exactly how close you are to that limit. Keeping your Midjourney prompts concise and well-structured generally produces better image results anyway.
No. All counting and estimation happens entirely in your browser using JavaScript. Your prompt text never leaves your device and is not transmitted to any server or API. You can verify this by disconnecting from the internet — the tool will continue to work offline.
As a general guideline, leave at least 50–70% of the context window available for the model's response. For example, if you're using a model with a 128K token limit, aim to keep your prompt under 40–60K tokens. This ensures the model has enough room to generate a complete, high-quality response without being truncated.