Glossary

What Is LLM?

Large Language Model

An LLM is a neural network trained on massive text datasets to understand and generate human language. GPT-4, Claude, Gemini, and Llama are all LLMs. They power chatbots, code generation, translation, summarization, and virtually any text-based AI task.

How LLM Works

LLMs learn language patterns by training on trillions of tokens from books, websites, and code. They predict the next token in a sequence — but this simple objective produces emergent abilities like reasoning, coding, and creative writing at scale.

Key LLMs in 2026: GPT-4o (OpenAI), Claude 4 (Anthropic), Gemini 2 (Google), Llama 3 (Meta, open-source). They differ in context window size, reasoning ability, coding skill, and pricing. Most developers access them through APIs.

Why Developers Use LLM

Developers integrate LLMs via APIs for chatbots, code assistants, content generation, data extraction, and search. The pattern: send a prompt to the API → get a completion back → display to user or process further.

Key Concepts

  • Context Window — The maximum text length the model can process — ranges from 8K to 200K+ tokens
  • Tokens — Text chunks the model processes — roughly 4 characters per token in English
  • Temperature — Controls output randomness — 0 for factual, 0.7 for creative, 1.0 for wild
  • System Prompt — Instructions that shape the model's behavior — persona, rules, output format

Calling an LLM API

python
from anthropic import Anthropic

client = Anthropic()
message = client.messages.create(
    model='claude-sonnet-4-20250514',
    max_tokens=1024,
    system='You are a senior Python developer.',
    messages=[
        {'role': 'user', 'content': 'Write a retry decorator with exponential backoff'}
    ]
)
print(message.content[0].text)

Learn LLM — Top Videos

LLM Educators

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Frequently Asked Questions

What is the best LLM for coding?

Claude (Anthropic) and GPT-4o (OpenAI) lead for code generation in 2026. Claude excels at long code contexts; GPT-4o has broader tool integrations. Both significantly outperform open-source alternatives.

Can I run LLMs locally?

Yes, with models like Llama 3 and Mistral. You need a decent GPU (16GB+ VRAM) for reasonable performance. Ollama and llama.cpp make local deployment straightforward.

Want a structured learning path?

Plan a LLM Lesson →

Related Terms

ChatGPTTransformerTokenPrompt EngineeringFine-Tuning

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