This application provides a method and an apparatus for training an intelligent model. The method includes: A central node and a plurality of participant node groups jointly perform training of the intelligent model, the intelligent model consists of a plurality of feature models corresponding to a plurality of features of an inference target, participant nodes in one of the participant node groups train one of the feature models, and the training method is performed by a participant node, and includes: receiving, from the central node, first information that indicates an inter-feature constraint variable, where the inter-feature constraint variable represents a constraint relationship between different features; obtaining, based on the inter-feature constraint variable, a model parameter of a first feature model, and first sample data by using a gradient inference model, gradient information corresponding to the inter-feature constraint variable; and sending the gradient information to the central node.