A processor-implemented method with multi-task processing includes: obtaining weights of a first neural network; obtaining first delta weights of a second neural network that is fine-tuned from the first neural network, based on a target task; performing an operation of the second neural network on first input data, based on sums of the weights of the first neural network and the first delta weights; obtaining second delta weights of a third neural network that is fine-tuned from the first neural network, based on a change of the target task; replacing the first delta weights with the second delta weights; and performing an operation of the third neural network on second input data, based on sums of the weights of the first neural network and the second delta weights, wherein the first delta weights comprise difference values in the weights of the first neural network and weights of the second neural network, and the second delta weight comprises difference values in the weights of the first neural network and weights of the third neural network.