Last updated: April 5, 2026 · Core Concepts · by Daniel Ashford

What is Large Language Model (LLM)?

QUICK ANSWER

An AI system trained on massive text data to understand and generate human language.

Definition

A Large Language Model (LLM) is a type of artificial intelligence trained on billions of words of text using deep learning techniques, primarily the transformer architecture. LLMs learn statistical patterns in language that allow them to generate coherent text, answer questions, write code, translate languages, and perform reasoning tasks.

How It Works

Modern LLMs like GPT-5, Claude Opus 4, and Gemini Ultra contain hundreds of billions of parameters. They are trained in two phases: pre-training on massive internet text corpora, and fine-tuning with human feedback (RLHF) to make outputs helpful, harmless, and honest. The "large" in LLM refers to both the model size and the training data volume.

Example

When you ask ChatGPT to "explain photosynthesis," the LLM generates a response by predicting the most likely next word, thousands of times in sequence, drawing on patterns learned during training.

Related Terms

Transformer
The neural network architecture behind all modern LLMs.
Parameters
The numerical weights inside an LLM that encode its learned knowledge.
Tokens
The basic units of text that LLMs process — roughly 3/4 of a word.
Fine-Tuning
Customizing a pre-trained LLM on your specific data to improve performance for your use case.
RLHF (Reinforcement Learning from Human Feedback)
The training technique that makes LLMs helpful and safe by learning from human preferences.

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Daniel Ashford
Founder & Lead Evaluator · 200+ models evaluated