Tokens
The bite-sized chunks of text that AI models read and generate, like words or word fragments. They're how AI counts and processes language.
What are Tokens?
Tokens are the small pieces of text that AI models break language into before processing it.
Think of them like LEGO blocks. A sentence gets split into tokens (which can be whole words, parts of words, or even punctuation), the AI processes those blocks, then reassembles them into a response. "I love AI" becomes three tokens: "I", "love", "AI".
Every AI request you make burns tokens. Most models charge per token (input + output), so knowing your token count matters for budgeting. A rough rule: 1 token equals about 4 characters or ¾ of a word in English. That 500-word blog post? Around 667 tokens.
Use OpenAI's Tokenizer to check counts before you send requests. Different languages tokenize differently (Spanish uses more tokens per word than English), which affects your API costs.
Good to Know
1 token ≈ 4 characters or ¾ of a word in English
AI models charge per token (both input and output)
Different languages use different token counts for the same meaning
Most modern models support context windows of 100K+ tokens
Token limits determine how much text you can send in one request
How Vibe Coders Use Tokens
Estimating API costs before building a feature that summarizes user content
Checking if your prompt fits within a model's context window
Optimizing prompts to use fewer tokens and cut your monthly bill
Understanding why your 10-page document gets truncated mid-response
Frequently Asked Questions
Related Terms
The text instruction you give an AI model to tell it what you want it to do, like asking ChatGPT to write code or explain a concept.
A technique that lets AI models search your documents or databases before answering, combining real-time data retrieval with text generation.
Meta's open-source family of large language models you can download, customize, and run without API costs or vendor lock-in.
OpenAI's conversational AI that can write, code, analyze data, and help you build faster through natural language prompts.
A specialized database that stores data as mathematical vectors (embeddings) to enable fast semantic search and AI-powered similarity matching.
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