The post discusses a theoretical chip architecture that could potentially outperform Nvidia in LLM inference by utilizing LPDDR memory and older TSMC nodes instead of high-bandwidth memory (HBM). Technical analysis of the Nvidia H100 and Blackwell chips suggests they are "unbalanced" for decoding tasks, carrying a "98% tax" in hardware latency when moving small data packets like those in Llama 3.3. The author argues that by balancing memory bandwidth, FLOPs, and interconnect latency, a new architecture could beat Nvidia on decode performance using a fraction of the silicon.