Glossary · Definition
LLM (Large Language Model)
An LLM (Large Language Model) is a transformer-based neural network trained on huge text datasets to predict the next token. ChatGPT, Claude, Gemini, DeepSeek — all are LLMs.
Definition
An LLM (Large Language Model) is a transformer-based neural network trained on huge text datasets to predict the next token. ChatGPT, Claude, Gemini, DeepSeek — all are LLMs.
What it means
All modern LLMs use the transformer architecture introduced in 2017. They're trained in two main phases: pretraining on web-scale text (predicting the next token), then post-training (RLHF, DPO, instruction tuning) to make them helpful, harmless, and honest. Frontier models in 2026 have 100B-2T+ parameters and are trained on trillions of tokens.
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Why it matters
LLMs underlie nearly all of generative AI in 2026 — chatbots, coding agents, search, customer support bots, summarization tools. Understanding what they are (and aren't — they're statistical patterns, not reasoning engines) helps you set realistic expectations and avoid hallucination-related failures.
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Frequently asked questions
Frontier LLMs in 2026?
Closed: Claude Opus 4.7, GPT-5, Gemini 3 Pro, Grok 4. Open-weight: DeepSeek V3.2, Kimi K2, Llama 4 Maverick, Qwen 3.5.
Are LLMs the same as 'AI'?
No — LLMs are one type of AI. Image gen (diffusion models), video gen (different transformer variants), and traditional ML (random forests, gradient boosting) are also AI.
Related terms
- DefinitionAI agentAn AI agent is an LLM running in a loop: think → call a tool → observe the result → think again. The loop continues until the task is done or a stopping condition is hit.
- DefinitionContext windowThe context window is the maximum amount of text (in tokens) an AI model can process in a single request — combining your system prompt, conversation history, and output. Past the limit, the model can't 'see' earlier content.