What is Large language model (LLM)?
The type of AI behind chatbots like ChatGPT, Gemini and Claude, trained on huge amounts of text to predict and generate language.
An LLM learns how language works by reading an enormous amount of text, then generates answers one small piece (a token) at a time, each time picking a likely next piece based on everything before it.
Because it predicts plausible text rather than looking facts up, an LLM can sound confident and still be wrong. That is why newer assistants add web search, citations and “reasoning” modes, and why you should double-check facts, numbers and quotes.
Why it matters
Asking an LLM to “summarise this article” is a strength. Asking it for today's gold price without web search is a weakness — it may invent a number.
Related terms
The small chunks of text an AI model reads and writes — roughly a word or part of a word. Limits and pricing are counted in tokens.
How much text an AI model can keep in mind at once — your conversation, uploaded files and its own replies combined.
When an AI confidently states something false — a fake fact, quote, source or statistic.
An AI model that works through a problem step by step before answering, trading speed for accuracy on hard questions.
