The performance of our MiMiC-based QM/MM implementation was tested in a number of benchmarks. These report the speedup (i.e. S N = t 1 t N where N is the number of compute nodes and t 1 is the timing of one node), strong scaling efficiency (P E = S N N * 100%), and absolute timing per MD step. As a rule of thumb, we define a scaling limit as the amount of cores at which the parallel efficiency stays above a 70% threshold. The systems differ by their size and complexity (see below). They are treated using either the BLYP or B3LYP exchange-correlation (XC) functionals. The former is a typical example of a generalizedgradient approximation (GGA), which scales linearly in a plane wave basis, whereas the latter constitutes an example of a hybrid functional, which scales quadratically with respect to the numbers of orbitals in plane waves. The hybrid functional implementation in CPMD can exploit thousands of cores, 9 thus using B3LYP allows us to examine the scaling limits of MiMiC under highly parallel conditions.