What Are Parameters in an AI Model?
In AI, parameters are the internal numerical values — mainly the weights of a neural network’s connections — that a model learns during training. They store what the model has learned. Large language models can have billions of parameters, which is often used as a rough measure of model size.
Parameters vs. Hyperparameters
Parameters are learned from data. Hyperparameters, such as the learning rate or number of layers, are settings chosen by people before or during training.
Is Bigger Always Better?
More parameters can capture more complex patterns, but model quality also depends heavily on training data and training methods, and larger models cost more to run.
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Last updated: September 29, 2026. This definition is for general educational purposes only. It is not financial, investment, tax, legal, or medical advice, and it does not recommend any product or course of action. For decisions about your own situation, consult a qualified professional.