Fragment-based approximations, anchored in the many-body expansion (MBE), are an appealing means to sidestep the steep nonlinear scaling of ab initio quantum chemistry. There is also growing interest in using the MBE to systematically decompose interaction energies in molecular liquids, 2-5 biomolecules, and other complex systems, as a means to generate training data for machine learning applications. A growing body of work, however, demonstrates that care must be taken to avoid error accumulation in MBE-based methods. The enormity of the resource requirements for datahungry machine learning applications places a premium on low-cost electronic structure models such as density functional theory (DFT), yet we have recently demonstrated that self-interaction error (SIE) causes catastrophic failure of the DFT-based MBE. In the present work, we illustrate how SIE is intermingled with quadrature grid errors, in a manner that is unique to DFT calculations based on the MBE and does not manifest in conventional electronic structure calculations. The functionals most strongly affected are meta-generalized gradient approximations (meta-GGAs), which represent many of the most accurate contemporary exchange-correlation functionals. Using calculations on F -(H 2 O) 15 clusters, we demonstrate herein that grid-based error dominates higher-order MBE calculations that employ meta-GGAs. This obfuscates other sources of error, such as SIE, which must be addressed for accurate DFT-MBE calculations. Improving the grid quality brings SIE-based delocalization error to the fore.