An artificial intelligence inference chip accelerates the mathematical operations used after a model has been trained. Its architecture can optimize matrix multiplication, memory movement, numerical precision, batching, and specialized kernels so deployed models respond with lower latency or higher throughput.
The value of an inference chip depends on the full serving system. Software compatibility, memory capacity and bandwidth, networking, power consumption, model support, and utilization can matter as much as the processor's advertised peak performance.
