What is a Large Language Model (LLM)?
Updated August 2026 · ~5 min read
A Large Language Model (LLM) is a type of artificial intelligence model trained on vast amounts of text data to understand and generate human language. LLMs use a neural network architecture called the Transformer, introduced by Google in 2017.
**How LLMs Work:** LLMs are trained to predict the next token (word or part of a word) given a sequence of previous tokens. Through this simple objective, they learn grammar, facts, reasoning abilities, and even coding skills.
**Key Concepts:** - **Parameters**: The "size" of the model, measured in billions of parameters. GPT-4 has ~1.8 trillion parameters. - **Context Window**: How much text the model can "see" at once. Modern models handle 100K–10M tokens. - **Tokens**: The basic units of text. 1 token ≈ 0.75 words in English. - **Fine-tuning**: Additional training on specific data to specialize the model.
**Popular LLMs in 2026:** GPT-5.5 (OpenAI), Claude Opus 4.7 (Anthropic), Gemini 3.1 Pro (Google), DeepSeek V4 Pro (DeepSeek), Qwen 3.7 Max (Alibaba).
**Use Cases:** Chatbots, code generation, content creation, data analysis, translation, research, and education.
Related Articles
A practical guide to choosing the right AI model for your project. Compare intelligence, speed, cost...
AI Model Pricing Explained — How Much Do Models Cost?Understand AI model pricing: input tokens, output tokens, caching, batch processing, and how to opti...
Reasoning Models Explained — How AI Thinks Before AnsweringWhat are reasoning models like o1, DeepSeek R1, and Claude thinking? How do they work and when shoul...