Large Language Models (LLMs)
LLMs explained — how large language models like GPT-5, Claude 4, Gemini 2, and Llama 4 work, and how to pick the right one for each task.
A large language model is a neural network trained on trillions of words that predicts the next token in a sequence. That single ability powers chat, writing, coding, search and reasoning.
What you'll learn
- How transformer architecture works
- Tokens, context windows, temperature
- Top LLMs of 2026: GPT-5, Claude 4, Gemini 2, Llama 4, Grok 3
- Open source vs closed source LLMs
- How to pick the right LLM per task
- Cost, latency and reasoning trade-offs
Recommended tools
Deep-dive guides
Frequently asked questions
Which LLM is best in 2026?+
GPT-5 leads for general reasoning and multimodal. Claude 4 wins for long-form writing and 200k+ context. Gemini 2 leads for Google Workspace and 1M context. Grok 3 leads on real-time X data.
What is a context window?+
The maximum amount of text an LLM can process at once. GPT-5 handles 400k tokens, Claude 4 handles 200k, and Gemini 2 handles 1M+ — roughly 750,000 words.
Want Large Language Models (LLMs) training for your team?
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