An LLM (large language model) is an AI trained on huge amounts of text to understand and generate human language. LLMs power chatbots like ChatGPT, Gemini and Claude by predicting the most likely next words in a response.

What is a large language model?

An LLM is a type of AI model trained on enormous amounts of text — books, websites, code and more. By learning statistical patterns in language, it can answer questions, write, summarise, translate and code. ‘Large’ refers to the model’s size (billions of parameters) and the scale of its training data.

How do LLMs work?

At their core, LLMs predict the next ‘token’ (a word or word-piece) given the text so far. Repeating this prediction builds fluent sentences and paragraphs. They do not store facts like a database; they encode patterns, which is why they can be fluent yet occasionally wrong.

What are their strengths and limits?

LLMs are excellent at language tasks — drafting, summarising, explaining, coding. Their limits are real: they hallucinate, reflect training biases, and have a knowledge cut-off unless connected to live search. AI can fabricate facts, figures and citations with total confidence (a “hallucination”). Treat AI output as a draft and verify anything important against a reliable source — this matters most for medical, legal, financial and academic use. Many tools add web search or your own documents to ground answers in current, specific information.

If you find yourself juggling a separate subscription for chat, automation, transcription and image generation, one option worth knowing is a single platform that runs them together — osFoundry is one such agentic AI platform that consolidates chat, agents and internal apps in one workspace, with a bring-your-own-key model so you choose the underlying AI.

This article is general information, not professional, legal or financial advice. AI tools, prices and availability change fast — verify current details on the official source before you rely on them.