A comparison method for a chip product, the method comprises: acquiring a comparison task implemented in a software system for at least two chip products, and acquiring a comparison feature responsive to an operation of a user, wherein the comparison feature comprises three-dimensional position coordinates and parameter information of the chip products required to be compared; for each chip product, acquiring a comparison result corresponding to the comparison feature from a three-dimensional stereoscopic model corresponding to the chip product, wherein the comparison result comprises slice images and the parameter information of the chip product, wherein the three-dimensional stereoscopic model corresponding to each chip product is a three-dimensional model which is recombined and constructed by a neural network according to a slice sequence of the chip product, the neural network comprising a residual network, a U-net network model and a multi-granularity network model, the slice sequence comprises a plurality of continuous slice images acquired by slicing the chip product and image feature of each slice image is embedded into a three-dimensional geometric shape for obtaining the three-dimensional stereoscopic model; and displaying the comparison result corresponding to each chip product so that the same target region in each chip product is displayed simultaneously; wherein the three-dimensional stereoscopic model corresponding to the chip product is acquired by: inputting each slice image in the slice sequence into the residual network so as to be subjected to feature extraction to obtain a first image feature of each slice image; segmenting the slice sequence through the U-net network model, and inputting each slice image in the segmented slice sequence into the residual network so as to be subjected to feature extraction to obtain a second image feature of each slice image; merging the first image feature and the second image feature of each slice image to acquire an image feature of the slice image; and constructing the three-dimensional stereoscopic model corresponding to the chip product by adopting the multi-granularity network model according to the slice sequence and the image feature of each slice image; wherein the image feature includes at least one of color feature, texture feature, shape feature, and depth feature. acquiring a comparison task implemented in a software system for at least two chip products, and acquiring a comparison feature responsive to an operation of a user, wherein the comparison feature comprises three-dimensional position coordinates and parameter information of the chip products required to be compared; for each chip product, acquiring a comparison result corresponding to the comparison feature from a three-dimensional stereoscopic model corresponding to the chip product, wherein the comparison result comprises slice images and the parameter information of the chip product, wherein the three-dimensional stereoscopic model corresponding to each chip product is a three-dimensional model which is recombined and constructed by a neural network according to a slice sequence of the chip product, the neural network comprising a residual network, a U-net network model and a multi-granularity network model, the slice sequence comprises a plurality of continuous slice images acquired by slicing the chip product and image feature of each slice image is embedded into a three-dimensional geometric shape for obtaining the three-dimensional stereoscopic model; and displaying the comparison result corresponding to each chip product so that the same target region in each chip product is displayed simultaneously; wherein the three-dimensional stereoscopic model corresponding to the chip product is acquired by: inputting each slice image in the slice sequence into the residual network so as to be subjected to feature extraction to obtain a first image feature of each slice image; segmenting the slice sequence through the U-net network model, and inputting each slice image in the segmented slice sequence into the residual network so as to be subjected to feature extraction to obtain a second image feature of each slice image; merging the first image feature and the second image feature of each slice image to acquire an image feature of the slice image; and constructing the three-dimensional stereoscopic model corresponding to the chip product by adopting the multi-granularity network model according to the slice sequence and the image feature of each slice image; wherein the image feature includes at least one of color feature, texture feature, shape feature, and depth feature.