LLM (Large Language Model)
LLM & Language ModelsA type of AI model trained on massive amounts of text data that can understand, generate, and reason about human language. GPT-4, Claude, Gemini, and Llama are all LLMs.
Large Language Models are the technology behind the AI revolution that started with ChatGPT in late 2022. An LLM is a neural network trained on billions of words from the internet, books, code, and other text sources, enabling it to generate human-like text, answer questions, write code, translate languages, and reason through complex problems.
The 'large' in LLM refers to the number of parameters (learned values) — ranging from a few billion (Llama 8B) to hundreds of billions (GPT-4, estimated at 1.8 trillion). More parameters generally mean more capability, but also more expensive to run.
The major LLM families are: GPT (OpenAI), Claude (Anthropic), Gemini (Google), Llama (Meta, open-source), and Mistral (Mistral AI, open-source). Each has different strengths — Claude excels at long-form analysis, GPT-4 at breadth, Gemini at multimodal tasks, and Llama at local deployment.
Real-World Example
ChatGPT, Claude, Gemini, Perplexity — virtually every conversational AI tool on Coda One is powered by an LLM under the hood.
Related Terms
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FAQ
What is LLM (Large Language Model)?
A type of AI model trained on massive amounts of text data that can understand, generate, and reason about human language. GPT-4, Claude, Gemini, and Llama are all LLMs.
How is LLM (Large Language Model) used in practice?
ChatGPT, Claude, Gemini, Perplexity — virtually every conversational AI tool on Coda One is powered by an LLM under the hood.
What concepts are related to LLM (Large Language Model)?
Key related concepts include Token, Context Window, Transformer, Foundation Model, Pre-training, Fine-tuning. Understanding these together gives a more complete picture of how LLM (Large Language Model) fits into the AI landscape.