Local Models and Agents Redefine AI PC Hardware

The first wave of AI PCs was largely defined by neural processing unit performance. Microsoft reinforced that approach when it introduced Copilot+ PCs on May 20, 2024, requiring an NPU capable of at least 40 trillion operations per second. That benchmark gave manufacturers and buyers a simple measure of whether a computer could run AI features locally, but it did not fully account for the demands of larger models.

The industry’s focus is now shifting toward memory capacity, bandwidth and unified memory architecture as local large-language models and multi-agent workloads become more prominent. These applications require processors to move large volumes of model data efficiently and allow CPUs, GPUs and NPUs to share memory without repeated transfers. As a result, peak NPU throughput alone is becoming a less useful definition of an AI PC, while system-level performance is emerging as the new standard.