We provide an overview of activities and results in the development of a performance-portable atmospheric model for research applications and numerical weather prediction. The model framework considers a full Python implementation with the GT4Py (GridTools for Python) domain-specific library encompassing the non-hydrostatic finite-volume dynamical core and tightly coupled physical process parametrizations. GT4Py is employed with 3D structured grids for regional domains and with horizontally unstructured meshes for global domains. We highlight selected numerical, software and high-performance aspects of the model, and address the porting of physical parametrizations. Furthermore, we present results from performance and scalability testing across different GPU based supercomputers, basic model validation, and exciting high-resolution applications in Alpine terrain using the developed moist large-eddy simulation configuration.