The present disclosure provides a method, and an apparatus for model distillation, relates to the technical field of artificial intelligence, and in particular, relates to technical fields of deep learning and computer vision. A specific implementation includes: obtaining a batch of teacher features corresponding to a teacher model and a batch of student features corresponding to a student model; determining a set of teacher similarities corresponding to the batch of teacher features and a set of student similarities corresponding to the batch of student features; determining weights of loss values of features of images based on difference values corresponding to the images; and weighting a loss value of a feature of each image in a batch of images, training the student model by using a weighting result. The present disclosure may use the difference values between the feature similarities of the student model and the feature similarities of the teacher model to determine the weights of the loss values. The distillation process of the present disclosure may improve the detection capabilities of the models, reduce the delay of the execution devices, and reduce the occupation and consumption of computing resources such as memories.