This paper compares Monte Carlo approaches and fast Fourier transform (FFT) methods to efficiently calculate small‐angle scattering (SAS) profiles from large morphological models. These methods enable calculation of SAS from complex nanoscale morphologies commonly encountered in modern polymeric and nanoparticle‐based systems which have no exact analytical representation and are instead represented digitally using many millions of subunits, so that algorithms with linear or near‐linear scaling are essential. The Monte Carlo method, referred to as the Monte Carlo distribution function method (MC‐DFM), is presented and its accuracy validated using a number of simple morphologies, while the FFT calculations are based on the fastest implementations available. The efficiency, usefulness and inherent limits of DFM and FFT approaches are explored using a series of complex morphological models, including Gaussian chain ensembles and two‐phase three‐dimensional interpenetrating nanostructures.