What is an LLM? Large Language Models Explained (2026)
TLDR
An LLM (large language model) is a type of AI trained on massive amounts of text to understand and generate human language. ChatGPT, Claude, and Gemini are all built on LLMs.
A large language model is a neural network trained on vast quantities of text, often hundreds of billions of words. Through this training, it learns patterns in language: grammar, facts, reasoning styles, coding conventions, and much more.
The "large" in LLM refers to both the size of the training data and the number of parameters (adjustable values) in the model. GPT-4 is estimated to have over a trillion parameters, though exact figures are not publicly disclosed.
LLMs work through a mechanism called attention, which allows the model to weigh how relevant each word in a sentence is to every other word. This gives LLMs the ability to understand context, tone, and nuance across long passages of text.
The key insight behind modern LLMs is that predicting the next word from a large enough dataset develops rich representations of knowledge and reasoning, not just language patterns. This is why LLMs can solve math problems, write code, and reason about complex topics.
In practice
ChatGPT
Built on GPT-4o, one of OpenAI's LLMs. The model generates each word of its response by predicting what comes next given the conversation so far.
Claude
Anthropic's LLM, known for its large context window and strong writing. Claude 3.5 Sonnet can process up to 200,000 tokens in a single conversation.
Open-source LLMs
Meta's Llama models are open-source LLMs that anyone can download and run locally, enabling private AI without sending data to external servers.
Frequently asked questions
What is the difference between an LLM and AI?+
AI is a broad category. LLMs are a specific type of AI focused on language. There are many other types of AI including image recognition models, recommendation systems, and robotics controllers.
Can I run an LLM on my own computer?+
Yes. Smaller open-source models like Llama 3 and Mistral can run locally on a modern laptop. Larger models require powerful GPUs. Tools like Ollama make this accessible for non-technical users.
What makes one LLM better than another?+
Training data quality and quantity, model architecture, fine-tuning approach, and the human feedback used to align the model all contribute. Benchmarks help, but real-world performance varies significantly by task.
Bottom line
An LLM (large language model) is a type of AI trained on massive amounts of text to understand and generate human language. ChatGPT, Claude, and Gemini are all built on LLMs.
Put it into practice
Prompt packages that apply these concepts directly.