Large Language Model

A Large Language Model is a neural network trained on enormous volumes of text to predict and generate language. By learning statistical patterns across billions of words, an LLM can answer questions, summarize documents, compare products, and recommend brands in natural, conversational language. The models that matter most for brand visibility each draw on a mix of training data, retrieval from the live web, and built-in reasoning to construct an answer. Genezio tracks brand presence across the major engines and model families that users actually rely on today, including OpenAI's GPT-5.4, GPT-4.1, GPT-4o Mini, and the GPT-4o Search Preview, ChatGPT itself, Anthropic's Claude, Google Gemini, Google AI Overview and Google AI Mode, Microsoft Copilot, Perplexity, DeepSeek, and Grok. Because each engine has different training data, retrieval behavior, and answer style, the same query can surface very different brands from one model to the next, which is exactly why visibility has to be measured per-engine rather than assumed to be uniform. And because an LLM does not simply return a ranked list of links but synthesizes a single response, the question of whether your brand is mentioned, cited, or recommended is decided inside the model's generation process. Understanding how LLMs ingest, weight, and reproduce information is therefore the foundation of every AI-visibility strategy.