What is Parameters? Plain-English Definition

In more detail

Parameters are the billions of tiny internal dials inside a model. Training is the process of nudging every dial, over and over, until good answers come out. The finished pattern of dial settings is the model — its ‘knowledge’ lives entirely in those numbers.

Parameter count is AI’s favorite shorthand for size: more dials usually means more capability, but also more memory and higher running costs. It’s why small models fit on your phone while frontier models need warehouses full of specialized hardware.

📌 See it in action

Picture a recording-studio mixing desk with billions of sliders. Nobody sets them by hand — the training data pushes each slider a hair at a time, across millions of rounds, until the sound comes out clean. Ask why a model answered the way it did, and the honest reply is: that’s where the sliders ended up.

Goes with

Training Data →LLM →Quantization →

Now put the vocabulary to work.

Meet the models →Which AI is mine?