Major mobile hardware manufacturers are reallocating die area on flagship system-on-chip (SoC) designs to dedicated Neural Processing Units (NPUs). This design pivot allows complex machine learning inference to occur locally rather than relying on cloud API calls.
Thermal and Battery Trade-offs
Local model execution reduces network latency and bandwidth costs, though developers face tighter thermal throttling constraints. Hardware benchmarks show modern mobile NPUs processing small language models under 5-watt envelopes.