ASIC vs. GPU: Custom Silicon for LLM Inference

GPUs were designed for graphics rendering and adapted for machine learning, but they contain hardware overhead that isn't needed for model inference. This has led to the development of Application-Specific Integrated Circuits (ASICs).

ASICs are designed from the ground up for tensor calculations and memory bandwidth. By stripping away graphics pipelines, these specialized chips run model inference with significantly lower latency and power consumption.

Cloud giants are building their own custom ASICs to reduce reliance on third-party hardware. This vertical integration allows them to optimize host costs and offer highly competitive pricing for their API platforms.