An LLM is trained on enormous volumes of text and learns statistical patterns in how language is used: which words tend to follow which, how ideas are usually structured, how questions are usually answered. From that, it generates plausible next words, one at a time, fast enough to look like a conversation.
That single mechanism explains both its strengths and its limits. LLMs are excellent at fluent, coherent, context-aware language, drafting, summarising, explaining, translating. They are not databases and do not “look up” facts; they generate the statistically likely answer, which is why they can sound confident while being wrong.
For a business, the practical decision is rarely “which LLM is smartest.” It’s what you connect the model to (your data, your tools), what you constrain it from doing, and what you check before its output reaches a customer or a decision.