A thermoelectric generator (TEG) is studied by considering different leg structures of hollow/filled legs, using new cooling nanofluids, and analyzing the segmentation effect. TEG performance is characterized by power output, conversion efficiency, and exergy efficiency. This study shows the impact of different cooling nanofluids (TiO2, graphene, and Al2O3) on the performance of the thermoelectric generator. Furthermore, in the comparative analysis of nanofluid cooling enhancement for TEG, different hollow/filled thermoelectric legs recently proposed in the literature are considered. Likewise, three segmentation types are used, 2n-2p, 1n-2p, and 2n-1p, thus will be compared with the results of the unsegmented legs. This study calculates the performance of thermoelectric leg structures through a validated numerical simulation on the ANSYS Workbench (modeling, design, and simulation). In addition, the optimal working conditions are evaluated. This study found that quenching of nanofluids can improve TEG performance by up to 17% compared to distilled water. However, the performance improvement of the TEG for each nanofluid is small between them. Furthermore, segmentation of n-type thermocouples improves efficiency and exergy, whereas segmentation of p-type thermocouples improves output power. The segmentation enhances performance by up to twice that of non-segmented leg structures; hollow structures are better performers. In the results, it is reported that the 2n-1p segmentation is the one with the best performance, reaching a maximum energy efficiency of 38%. The triangular leg structure improves performance by up to 75% compared to the rectangular and square leg structures. Likewise, using TiO2 is the best cooling option with nanofluids since it improves performance by 17% compared to distilled water. Furthermore, the results of cooling nanofluids for TEG performance are useful for the design of thermoelectric leg structures and stimulate further research.