In this work we analyze and benchmark the effect of partial occupations and the static subspace approximation on RPA and GW calculations, demonstrating that our implementation enables accurate GW and RPA calculations for a variety of systems, including metals, at scale. To this end, we first briefly detail our method developments within the BerkeleyGW code that decrease the computational demands of RPA and GW, which include the implementation of partial occupations into the computation of the RPA polarizability and the selfenergy operator, and the implementation of the static subspace approximation to the RPA polarizability. Then, we explore the convergence behavior of RPA total energies with respect to key computational parameters for a number of catalytically-relevant systems, including the size of the static subspace, k-point grid density, and partial occupation broadening.