To understand their properties, networks can be compared with those randomly generated from one or more network models. The network models introduced in this chapter, many of which are discussed at greater length later in the book, include the Bernoulli random graph, Erdős–Rényi mixture models, Chung–Lu graphs, small world networks, the configuration model, random geometric graphs, preferential attachment models, exponential random graph models, stochastic blockmodels, latent space models, random intersection graphs, graphon models, models for directed graphs and duplication–divergence models. Some basic properties of the models are considered, such as the distribution of the degree of a randomly chosen vertex and typical values of the clustering coefficient.