Mobile chipset developers are fundamentally redesigning System-on-Chip (SoC) architectures to support local execution of small language models. By running generative artificial intelligence tasks directly on handset hardware, manufacturers aim to reduce cloud latency, lower operational server costs, and enhance user data privacy.
Memory Bandwidth as the Primary Bottleneck
Integrating dedicated Neural Processing Units (NPUs) requires significant upgrades to mobile LPDDR memory bandwidth and capacity. Handset vendors are scaling baseline DRAM specifications, altering low-end and mid-tier device bill-of-materials costs.