--- language: en title: "LLM" description: "An LLM is a language model used to interpret and generate text. Learn the difference between a model and an assistant, and how it affects brand monitoring." canonical: "https://tropk.ai/en/resources/glossary/llm" last_modified: "2026-10-12T16:15:05.694Z" --- # LLM Reviewed on 2026-10-06. ## What it means LLM stands for Large Language Model. It is a model trained to learn language patterns and produce responses to inputs. It can interpret instructions, summarize materials, and generate text. In a search product, it works alongside other components, such as tools, document [retrieval](/en/resources/glossary/information-retrieval), and the product’s own controls. ## Why it matters for marketing For marketing, this distinction helps avoid confusing a model’s name with the entire experience a buyer uses. The same model can run in different products and configurations. An API-based collection, a conversation in an app, and a search with sources are not automatically equivalent, even if they share some of the generation technology. ## Example in practice A team asks an assistant about CRM tools. The response may combine information learned during training with recent research, if search was used. Another interface, using a related model without search, may describe an older offering. The contrast does not show that the company has changed; it shows different conditions for producing the response. ## How to apply or verify Record the platform, execution mode, and model when this information is available. Identify whether search was used, which sources appeared, and what context was present. When comparing results, treat changes to the model or product as possible changes in method. Save responses and dates so the investigation does not rely only on averages or isolated screenshots. ## Important distinctions An LLM is not a factual database that always returns the same record. It can make errors and vary its wording. Publishing content also does not mean that information is immediately added to training. To study brand representation, examine observable responses and sources, keeping hypotheses about the system’s internal workings separate. ## Sources and references - [The AI Search Glossary: A definition of 300+ terms]() — Profound - [Searching the web with ChatGPT]() — OpenAI ## Continue a leitura - [AI hallucination]() - [AI search]() - [RAG]() ## About the author [Vinicius Pacheco]() Responsible for Tropk’s technical content, focusing on crawling, indexing, structured data, and agent access to content. --- [All pages in Markdown]()