Design improvements in the conventional domestic oven can significantly impact food quality, energy efficiency, and user satisfaction. An experimental approach to understanding this complex coupled oven and food physics is resource intensive, and a computational system could be more efficient. We developed a novel computing framework that reduces resource needs while still coupling radiative and conductive heat transfer in oven walls, natural convection heat transfer in the oven cavity air, and multiphase porous media-based viscoelastic deformations in the food with cupcake baking as an example. Experimental data validate the model predictions of temperature in the cavity walls and temperature, moisture, oven rise, and color changes of the cupcake. The model comprehensively presents a mechanistic understanding of the energy fields inside the cavity and at the walls, the flow field in the cavity air, their transient changes with oven cycles, the internal physical condition of the cupcake during baking, the ingredient functionality and how the cake quality parameters are affected by the changes in oven settings, and spatial non-uniformity and recipe changes. The model enables a comprehensive mechanistic understanding of cupcake baking physics and its intricate relationship with ingredients. The novel computing framework for a universal cooking system coupling massive changes in mechanical and thermophysical properties with multiphase transport and expansion and specific results for the complex oven-food system will reduce development time and improve novel oven and food design and optimization.