Generative models have entered consumer mobile applications as a routine product feature, and their computational profile departs from that of the discriminative models that preceded them on the device. Image synthesis models exceed the memory and arithmetic budgets of a smartphone session, forcing the processing pipeline to span the device boundary. This review proposes a classification of the architectural trade-offs that govern such divided pipelines. Five axes organize the design space: the execution locus of each pipeline stage, the temporal contract the application makes with the user, the boundary that user data crosses, the governance of output quality, and the economics of a single invocation. The classification rests on a criterion that receives limited treatment in the deployment literature. The execution locus of a stage follows from how often a user invokes it within a session, the marginal cost of a remote call, and the technical feasibility of local execution; the latter enters the decision only after the frequency question has been settled. A stage repeated dozens of times within a single session belongs on the device, even when a server could perform it faster. The review also maps the mechanisms that substitute for automated assessment of generative output quality and identifies the absence of a computable proxy for aesthetic acceptability as an open problem. Observations from engineering practice in consumer mobile applications with generative image features supply illustrations for each axis. Those observations are descriptive and carry no controlled measurement.