What is a large language model (LLM)?
Updated · By Robert Breen
A large language model (LLM) is an AI model trained on a huge amount of text to predict what words should come next. That simple skill, at enormous scale, lets it answer questions, follow instructions, summarize documents and write drafts. LLMs power ChatGPT and most AI agents.
Why it matters for a small business
Whenever a tool reads a customer email and writes a reply, or turns a list of jobs into follow-up messages, an LLM is doing the language work. If you understand that it is predicting likely text from patterns, a lot of its behavior makes sense: why vague prompts get generic answers, why it can state something false fluently, and why giving it your facts changes everything.
For automation, the LLM is a part you plug in, not the whole system. On its own it only produces text. Connected to a workflow with triggers and tools, it can decide what to write and where to save it. Choosing which LLM to plug in, and paying for it, becomes a normal business decision.
In a real lesson: n8n AI Agent Tutorial: Save Social Media Ideas to Google Sheets
In the n8n AI Agent tutorial, you build a social media idea agent for BrightPath Marketing, a made-up agency. After you add the AI Agent node and its system prompt, a red warning appears on it. The voice-over explains why: an agent can plan, but it cannot think without a language model underneath it.
You fix that by clicking the + under Chat Model, choosing OpenAI Chat Model, connecting the API key you created, and picking gpt-5-mini from the Model dropdown. Now the agent has an LLM to do the reading and writing.
The rest of the canvas shows what the LLM is not. Simple Memory holds the conversation, the Google Sheets Tool writes rows, and the chat trigger starts each run. When you ask for three post ideas and then say "Yes, save those ideas to the sheet", the LLM writes the ideas and decides to call the Sheets tool, while the tool does the actual saving.
Try this lesson free or read the step-by-step guide.
Common confusions
LLM vs chatbot
An LLM is the engine. A chatbot like ChatGPT is a product built around it, with a chat window, memory features, file uploads and safety rules. The same LLM can sit behind a chatbot, an n8n agent or a website form.
LLM vs AI agent
An LLM only produces text. An AI agent wraps an LLM with tools and instructions so it can take actions, like adding a row to Google Sheets. In n8n you can see the difference: the agent node needs a separate chat model attached.
Does an LLM look things up?
Not by default. It answers from what it learned in training plus what you put in the prompt. Some products add web search or file lookup on top, which is a separate step.
Tips
- Start with a small, fast model for short text jobs and move up only when the output is not good enough.
- Put the facts the LLM needs in the prompt or system message; do not assume it knows your business.
Related terms
Where you use it: free lessons
- n8n AI Agent Tutorial: Save Social Media Ideas to Google Sheets (n8n, 12 min)
- Lovable + n8n: Build a Web App with an AI Backend (Lovable and n8n, 15 min)
- AI Email Responder: Draft Gmail Replies Automatically with n8n (n8n, 12 min)
Visual guide
Large language model (LLM) in a few slides, with the same guide written out as text.
Frequently asked questions
- Is ChatGPT an LLM?
- ChatGPT is an app that runs on OpenAI's large language models. People often use the names interchangeably, but the app adds features like chat history and file uploads on top of the model.
- Which LLM should I use in n8n?
- The lessons use gpt-5-mini for text jobs because it is fast and inexpensive, and gpt-4o where the agent has to read a photo. Start small and change models only when you have a reason.