A method for training a font generation model is described below. A source domain sample character and a target domain association character are input into a font generation network to obtain a target domain generation character. The target domain generation character and at least one of a target domain sample character or the target domain association character are input into a loss analysis network to obtain a first loss, and a parameter of the font generation model is adjusted according to the first loss. The source domain sample character and a random vector are input into the font generation network to obtain a random domain generation character. The random domain generation character and a random domain sample character are input into the loss analysis network to obtain a second loss, and the parameter is readjusted according to the second loss.