A token is a unit of text that a model processes. Token length depends on the tokenizer, language, and surrounding text; a word can be split into several tokens.
Many model APIs charge for input and output tokens. Shorter prompts can reduce token usage, but the bill also depends on output length, the model, and the provider's pricing rules.
No. This calculator uses its bundled GPT tokenizer for every price preset. Another provider or model may count the same text differently; no fixed accuracy margin is guaranteed.
Input tokens are what you send (your prompt + context). Output tokens are what the AI generates. Output tokens typically cost 2-5x more than input tokens because generation is more compute-intensive.
1. Remove filler words and redundant instructions. 2. Use concise examples. 3. Avoid repeating context. 4. Use shorter variable names in code prompts. 5. Set a max_tokens limit on responses.
Estimate text token usage and input cost before sending a model request.