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What Is an LLM (Large Language Model)? A Simple Guide (2025)

Learn what an LLM is, how it works, and why it powers almost every major AI tool today — from ChatGPT to Claude to Google Gemini.

Author

Marco Fazio
July 23, 2025

Ever wonder what’s behind ChatGPT, Claude, or Gemini? The answer is a Large Language Model, or LLM.

LLMs are the core technology behind modern AI tools — the reason they can write essays, summarize text, generate code, and answer questions in natural language.

This guide explains what an LLM is, how it works, and why it’s such a big deal in 2025.

What Is an LLM?

A Large Language Model (LLM) is an advanced type of artificial intelligence trained to understand and generate human language.

Think of it as:

A machine that has read billions of books, websites, and documents, and can now predict what words come next — in a smart, useful way.

It doesn’t just repeat text — it learns patterns, logic, grammar, facts, and reasoning from massive datasets.

What Can LLMs Do?

LLMs can:

  • Answer questions

  • Write emails, essays, blog posts

  • Translate languages

  • Summarize long text

  • Generate code

  • Explain complex topics

  • Simulate conversations

They're used in:

  • Chatbots (like ChatGPT, Claude, Gemini)

  • Search engines (Perplexity, Bing, Brave)

  • Customer support tools

  • Coding assistants (GitHub Copilot, Cody)

  • Business automations

How Do LLMs Work?

At the core, LLMs are trained to predict the next word in a sentence — over and over, across billions of examples.

During training:

  • They analyze huge datasets (books, Wikipedia, web pages, etc.)

  • They learn the structure, meaning, and logic of human language

  • They become capable of generating human-like text in response to prompts

Many are built using a transformer architecture (the “T” in GPT), which allows them to handle long, complex inputs efficiently.

Model

Developer

Known For

GPT-4o

OpenAI

ChatGPT, writing, coding, reasoning

Claude 3 Opus

Anthropic

Safer AI, thoughtful responses

Gemini 1.5

Google DeepMind

Real-time integration + Google tools

Mistral

Mistral AI

Open-source models

LLaMA 3

Meta

Foundation for many research tools

LLM vs Traditional AI

Feature

Traditional AI

LLM

Task type

Single-task (e.g. spam filter)

General-purpose text-based

Flexibility

Fixed use case

Learns and adapts

Input/output

Numbers or code

Natural language

Learning method

Manual rules/training

Self-learns from huge datasets

FAQs

Is ChatGPT an LLM?
Yes. ChatGPT is powered by OpenAI’s LLMs (GPT-3.5, GPT-4, GPT-4o).

Are LLMs conscious or sentient?
No. They process patterns — they don’t think or feel, even if they sound human.

How big are LLMs?
Some have hundreds of billions of parameters (think of these as “neurons”), and they’re trained on trillions of words.

Do LLMs make things up?
Yes — it’s called hallucination. They can confidently generate incorrect information, which is why fact-checking is still important.

Can I build or fine-tune my own LLM?
Yes. Open-source models like Mistral and LLaMA allow developers to build custom LLMs for specific use cases.

Final Thoughts

LLMs are the engines powering the AI revolution. They’ve made language — the most human thing we do — computable, scalable, and interactive.

Understanding how they work helps you use them better — whether you're writing a prompt, building a tool, or just curious about the future of intelligence.

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Marco Fazio Editor,
Latestly AI,
Forbes 30 Under 30

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