The energetics, structures and segregation of 98-atom AuPd nanoclusters are investigated using a genetic algorithm global optimization technique with the Gupta empirical potential (comparing three different potential parameterisations) followed by local minimizations using Density Functional Theory (DFT) calculations. A shell optimization program algorithm is employed in order to study the energetics of the highly symmetric Leary Tetrahedron (LT) structure and optimization of the chemical ordering of a number of structural motifs is carried out using the Basin Hopping Monte Carlo approach. Although one of the empirical potentials is found to favour the LT structure, it is shown that Marks Decahedral and mixed FCC-HCP motifs are lowest in energy at the DFT level.