{
  "id": "large-language-model",
  "code": "PTL-0102",
  "term": "Large Language Model",
  "aliases": [
    "LLM",
    "language model"
  ],
  "category": "foundations",
  "definition": "A large language model (LLM) is a neural network, usually a Transformer with billions of parameters, trained on very large text corpora to predict the next token, which lets it generate text and perform many tasks from a prompt.",
  "description": "The defining property is that a single model, without task-specific training, can translate, summarize, answer questions, write code, and follow instructions, with the task specified in the prompt. Most deployed LLMs are base models that have been further instruction-tuned and preference-tuned to behave as assistants. Their capabilities and their failure modes, such as hallucination and prompt sensitivity, both follow from next-token prediction over the prompt.",
  "example": null,
  "broader": [
    "foundation-model"
  ],
  "narrower": [
    "base-model"
  ],
  "related": [
    "token",
    "prompt",
    "in-context-learning"
  ],
  "introduced": null,
  "added": "2026-10-10",
  "sources": [
    {
      "title": "A Survey of Large Language Models",
      "authors": "Zhao et al.",
      "year": 2023,
      "url": "https://arxiv.org/abs/2303.18223"
    },
    {
      "title": "Language Models are Few-Shot Learners",
      "authors": "Brown et al.",
      "year": 2020,
      "url": "https://arxiv.org/abs/2005.14165"
    }
  ],
  "url": "https://protologue.com/t/large-language-model/",
  "citation": "Protologue. (2026). Large Language Model. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.4.0, PTL-0102). https://protologue.com/t/large-language-model/"
}