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What is an LLM (Large Language Model)? - Definition & Meaning

Learn what an LLM (Large Language Model) is, how large language models work, and why they form the foundation of modern AI assistants and chatbots.

Definition

An LLM (Large Language Model) is a large neural network trained on massive amounts of text to understand and generate human language. LLMs form the core of modern AI applications like ChatGPT, Claude, and Gemini, and can write text, answer questions, generate code, and perform complex reasoning.

Technical explanation

Large Language Models are based on the transformer architecture introduced in the paper "Attention Is All You Need" (2017). They consist of billions of parameters optimized during training on large text corpora via self-supervised learning. The training process includes pre-training (next-token prediction on large datasets), supervised fine-tuning (SFT) on instruction pairs, and Reinforcement Learning from Human Feedback (RLHF) for aligning with human preferences. Key concepts include tokenization (splitting text into tokens), attention mechanisms (weighing relationships between words), context windows (the maximum amount of text the model can process at once), and temperature (controlling output creativity). Popular open-source models include LLaMA, Mistral, and Phi, while commercial models include GPT-4, Claude, and Gemini. Inference can run locally via frameworks like Ollama and vLLM, or through cloud APIs.

How OpenClaw Installeren applies this

OpenClaw Installeren configures LLM connections as part of your AI assistant deployment. Our platform supports both cloud-based LLMs (OpenAI, Anthropic) and locally hosted models via Ollama on your own VPS. This lets you choose between maximum performance via cloud APIs or complete data privacy with local inference.

Practical examples

  • A customer service assistant using GPT-4 to understand complex customer questions and generate personalized answers based on product documentation and order history.
  • A content creation tool using an LLM to generate blog articles, product descriptions, and social media posts in multiple languages with a consistent brand voice.
  • A code assistant using an LLM to help developers write, review, and debug code, including explanations of complex algorithms.

Related terms

ai assistenttokenprompt engineeringfine tuningembedding

Further reading

What is an AI assistant?What is a token?What is fine-tuning?

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Frequently asked questions

GPT (Generative Pre-trained Transformer) is a specific family of LLMs developed by OpenAI. "LLM" is the umbrella term for all large language models, including GPT, Claude (Anthropic), Gemini (Google), LLaMA (Meta), and Mistral. So GPT is an LLM, but not every LLM is GPT.
Yes, with open-source models like LLaMA and Mistral, you can run an LLM locally using tools like Ollama. OpenClaw Installeren can configure this on your VPS, giving you full control over your data without depending on external cloud APIs.
Cloud-based LLMs charge per token (input and output). GPT-4 costs a few cents per 1000 tokens, while cheaper models like GPT-4o-mini cost a fraction of that. Locally hosted open-source models have no per-token costs but require server resources (GPU/RAM).

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