Comparison
Large Language Model vs Pretraining
Large Language Model and Pretraining are both common AI/LLM terms but cover different ideas. Here is a quick side-by-side.
When you would reach for Large Language Model
Large Language Model comes up when the question is fundamentally about foundations.
Claude Sonnet — Anthropic's general-purpose LLM.
When you would reach for Pretraining
Pretraining comes up when the question is fundamentally about training.
GPT-3 pretrained on ~300B tokens.
Frequently asked
What is the difference between Large Language Model and Pretraining?
Large Language Model: A large language model is a neural network trained on huge amounts of text to predict the next token in a sequence. GPT-4, Claude, and Gemini are all LLMs. Pretraining: Pretraining is the initial training phase where an LLM learns to predict the next token on trillions of tokens of general text. It produces a base model that can be adapted later.
When should I use Large Language Model vs Pretraining?
Large Language Model is the right concept when you are focused on foundations. Pretraining applies when you are focused on training.
Are Large Language Model and Pretraining the same thing?
No. Large Language Model is foundations; Pretraining is training. They are related but address different parts of the AI stack.