Separate Concerns explains on-device model constraints

Running AI models directly on mobile devices introduces distinct technical challenges compared to traditional GPU environments, including strict limits on memory, weight size, heterogeneous hardware, and slow on-device specialization times. To overcome these constraints, engineers must rely on specialized optimization strategies such as single-user sequential processing, extensive quantization of both weights and activations, and rewriting model graphs rather than writing low-level CUDA kernels. Open article →