Training neural network potentials (NNPs) capable of general Gezeolite modelling first requires the generation of a DFT dataset spanning all relevant parts of the configuration space. Previously, we demonstrated the development of general NNPs for silica and siliceous zeolites, including their reactive phase transformations, by selecting structurally distinct configurations from zeolite databases and active-learning simulations. The structure selection used farthest point sampling (FPS) with the smooth overlap of atomic positions (SOAP) descriptor to quantify the similarity between atomic environments. In this work, we focus on accurately modelling closeto-equilibrium (EQ) configurations of Ge-substituted zeolites. Therefore, we did not include high-energy structures required for the NNP training of reactive events in the current dataset. First, to cover the purely siliceous interactions, we used a subset of 22k EQ structures from the previously created silica database (33k structures in total, including high-energy structures). These structures were obtained from structure optimizations of a hypothetical zeolite database and lattice deformations applied to ten hypothetical and five existing zeolites (CHA, SOD, IRR, MVY, MTF) (see for details). This approach proved successful in generating a training database for the general modelling of zeolites. Subsequently, to cover the germanosilicate interactions, 10k EQ configurations were chosen by SOAP-FPS and Si atoms were randomly replaced by Ge atoms according to a randomly chosen Ge fraction (between 0 and 1, but with at least one Si/Ge atom in the unit cell). In addition, to sample EQ Ge-zeolites more systematically, we applied a set of lattice deformations to the aforementioned 15 frameworks, each with 9 randomly generated Ge substitutions covering Ge fractions between 0.25 and 0.75. We used all 70 permutations of possible strain tensors with strain rates of 1.5%, 3%, 4.5%, and 6% (see also for further details). Lastly, we used the same set of deformations for two GeO 2 polymorphs with tetrahedral Ge coordination (quartz-like structure) and hexagonally coordinated Ge (rutile-like structure).