GaussianCube is an innovative 3D radiance representation method that significantly advances 3D generative modeling through its structured and explicit representation. This technology achieves high-precision fitting by utilizing a novel density-constrained Gaussian fitting algorithm and optimal transport methods, rearranging Gaussian functions onto a predefined voxel grid. Compared to traditional implicit feature decoders or spatially unstructured radiance representations, GaussianCube boasts fewer parameters and higher quality, making 3D generative modeling more accessible.