AI “Word-to-Token” Estimator
Calculate token usage and estimated API costs for your AI prompts.
What are Tokens in 2026?
Tokens are the fundamental units of text that Large Language Models (LLMs) like Gemini and GPT-5 process. Instead of reading whole words, AI breaks text into “chunks” of characters. For example, a simple word like “apple” is 1 token, but a complex word like “tokenization” might be split into 2 or 3 tokens: “token” + “iza” + “tion”.
The 0.75 Rule
A general rule of thumb is that 1,000 tokens are approximately equal to 750 words. This estimator uses a more precise 2026 weighted average to give you a safer safety margin for API billing.
Code vs. Prose
Coding consumes significantly more tokens because symbols ( { } [ ] ; ), indentation, and unique variable names are often treated as individual tokens.
Optimization Tips for Creshy Users
- Remove Whitespace: Excess spaces and newlines in code can inflate token counts by up to 15%. Minify your data before sending it to an AI.
- System Prompt Efficiency: Keep your “Act as an Expert” instructions concise. These tokens are charged on every single turn of the conversation.
- Language Matters: Non-English languages (like Urdu or Arabic) often have a much higher token-to-word ratio (sometimes 3x higher) due to how tokenizers are trained.
Note: This is an estimate based on standard BPE (Byte Pair Encoding) algorithms. Actual token counts may vary slightly between Gemini, OpenAI, and Anthropic models.
