A new study from Apple examines modeling choices to optimize learned image codecs for human visual perception and runtime. Researchers tested several novel techniques to bridge the gap between theoretical quality and practical deployment. The findings provide a framework for building efficient, high-fidelity codecs. This represents an incremental improvement in computer vision efficiency.