The Swiss Energy Strategy 2050 pursues an ambitious transition to a more renew- able and efficient energy future, combining CO2 and energy saving targets with a phase-out of nuclear electricity generation. This transition poses challenges not only for the political domain, but also concerning the adequate modeling of technical and economic aspects, such as advancements in renewable energy and storage technologies, market liberalisation and international market integration, and the economic and social impacts of alternative economic instruments. This research investigates whether a Swiss carbon-free electricity sector remains feasible after the nuclear phase-out, how it would affect the Swiss economy and which policies would be needed to introduce the related transition towards renewable technologies and enhanced energy efficiency in an economically efficient way. To address such questions adequately, we need a modeling tool that provides both sufficient technological detail and consistent economic insight. With this in mind, we build a modeling framework that encompasses for Switzerland and its neighboring countries: • a multi-sectoral description of the economy based on general equilibrium and microeconomic theory, which represents electricity demand by economic sectors and households and illustrates effects of energy policy scenarios on welfare and other macroeconomic indicators. • a detailed representation of electricity supply technologies, resource potentials, costs, and international electricity trade, including grid-related restrictions, intra-day load curves, seasonal variations, and dynamic management of reservoirs. This framework consists of three coupled models: (1) GENESwIS, an energy-related dynamic Computable General Equilibrium (CGE) model of Switzerland, (2) CROSSTEM, an energy systems model that provides the technological details of electricity supply for Switzerland and its neighboring countries, and (3) GEMINI-E3, a dynamic-recursive CGE model, which adds the global climate policy and trade dimension to the framework. The coupling algorithm involves soft coupling of these three models for central equilibrium prices and quantities. At the workshop, we present work in progress. This includes important methodologi- cal issues that arise when trying to safeguard consistency in the coupling of prices between bottom-up and top-down models. Furthermore, we intend to present preliminary results from simulations with a coupled framework which consists of the first two models mentioned above, i.e. (1) the Swiss CGE model GENESwIS coupled with (2) the Swiss version of the electricity supply model CROSSTEM.