The embodiment of the present application discloses a face key point positioning model training method and device, an apparatus and a storage medium. The training method includes: constructing a CNN model for face key point positioning, wherein the number of convolution layers of the CNN model is greater than a first threshold, and the number of channels of the convolution layers is less than a second threshold; using the CNN model to perform face key point positioning on training samples, and obtaining prediction positions of face key points, wherein the face key points include n types, and the n is an integer greater than 1; calculating respective loss function values corresponding to the n types according to prediction positions and real positions of each type of face key points, and calculating a loss function value of the CNN model; and stopping training the CNN model and saving the CNN model if the loss function value of the CNN model is less than a preset threshold. The embodiment of the present application reduces the model size by constructing the elongated CNN model while ensuring that the positioning accuracy is not lost as much as possible.