{
  "@context": "https://schema.org",
  "@type": "QAPage",
  "canonical": "https://ireadcustomer.com/en/blog/what-is-an-llm-architecture-apis-and-local-run-guide",
  "markdown_url": "https://ireadcustomer.com/en/blog/what-is-an-llm-architecture-apis-and-local-run-guide.md",
  "title": "What Is an LLM? Architecture, APIs, and Local Run Guide",
  "locale": "en",
  "description": "Learn what Large Language Models (LLMs) are, how the Transformer architecture works, how to choose between Cloud APIs and open weights, and how to run Llama 3.1 locally.",
  "quick_answer": "An LLM (Large Language Model) is an AI trained on vast text data to process and generate language using Transformer-based next-token prediction, deployable via managed Cloud APIs or hosted locally with open weights.",
  "summary": "An LLM (Large Language Model) is an artificial intelligence model trained on massive text corpora using deep learning techniques to understand, generate, and process human language through next-token prediction. Unlike traditional rule-based Natural Language Processing systems, modern LLMs leverage transformer architectures to capture nuanced reasoning and contextual relationships across diverse tasks. For builders, software engineers, and technology professionals, understanding what an LLM is represents only the first step. The critical architectural decision is determining whether to connect",
  "faq": [
    {
      "question": "What does LLM stand for?",
      "answer": "In computing and AI, LLM stands for Large Language Model. In legal studies, it conventionally abbreviates Legum Magister (Master of Laws)."
    },
    {
      "question": "What is the difference between AI and ML?",
      "answer": "Artificial Intelligence (AI) is the broader discipline of building machines capable of intelligent behaviors. Machine Learning (ML) is a subset of AI where systems discover patterns from data autonomously rather than relying on hand-crafted rules."
    },
    {
      "question": "Which process helps LLMs communicate more effectively with humans?",
      "answer": "Instruction fine-tuning combined with Reinforcement Learning from Human Feedback (RLHF) steers raw base models toward conversational, helpful, and safe dialogue structures."
    },
    {
      "question": "What types of Machine Learning models exist?",
      "answer": "Core categories include Supervised Learning (classification, regression), Unsupervised Learning (clustering, dimensionality reduction), and Deep Neural Networks (CNNs, RNNs, and Transformers used in LLMs)."
    }
  ],
  "tags": [
    "LLM",
    "Llama 3.1",
    "Ollama",
    "Open Weights",
    "Artificial Intelligence",
    "Local AI"
  ],
  "categories": [],
  "source_urls": [
    "https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct",
    "https://ollama.com/library/llama3.1"
  ],
  "datePublished": "2026-10-17T08:08:34.531Z",
  "dateModified": "2026-10-17T08:08:34.552Z",
  "author": "Naruebet Aungsirikulthumrong"
}