LLM (Large Language Model)

A large language model is a neural network with billions of parameters trained on enormous text corpora to predict the next token given the preceding ones. That single objective — next-token prediction — turns out to be enough to learn grammar, facts, reasoning patterns, code, and conversation.

The frontier models everyone talks about (GPT, Claude, Gemini, Llama, Mistral) are all LLMs. They differ in training data, fine-tuning approach, safety alignment, modality (text-only vs. multimodal), and price. For most production work, the choice of LLM matters less than your prompting, retrieval, and evals — but for hard tasks, the gap between a frontier model and a small model is real and measurable.