Abstract In this work we present the cooperative coevolution of multi-layer generalized perceptrons. This model is based on the cooperation of different subpopulations of modules, each one being a generalized multi-layered perceptron. In some previous works we have developed a modular cooperative coevolutive model for evolving multi-layer perceptrons with two hidden layers. This model performs very well but tends to generate big networks. In the present paper we show the results of substituting these multi-layer perceptrons by generalized multi-layer perceptrons, which allow a more compact representation of networks. The use of generalized multi-layer perceptrons improved the performance of the evolutionary model with regard to the evolution of other kinds of networks. Another improvement was that the networks obtained were much smaller. The comparison proved statistically significant by means of a Student's t-test.