Hardware and benchmarking utilities

Running models locally pushes hardware in ways most everyday software does not. Memory fills up, the graphics card runs at full load for minutes at a time, and a laptop can get hot enough to slow itself down. Small monitoring and benchmarking utilities show what is actually happening, which is the fastest way to tell why a model is slow.

The most useful number is memory. On a PC, watch how much video memory the graphics card is using as a model loads. If it fills completely, part of the model spills to system RAM and speed drops sharply. On an Apple silicon Mac, watch total memory pressure, since the CPU and GPU share one pool. A monitor running alongside your model app makes these limits visible within seconds.

Load and temperature come next. A GPU that sits well below full use while a model runs usually means the bottleneck is elsewhere: the CPU, a slow drive during loading, or a setting that keeps work off the GPU. High temperatures on a laptop can trigger throttling, where the chip slows itself to cool down, so long jobs may run slower than short tests.

Benchmarks have a narrower role. A general AI benchmark gives a rough sense of how one device compares with another on standard tasks, which helps when choosing hardware. It does not predict exactly how a particular model will run in a particular app, because drivers, model formats and settings all matter. Use benchmarks to compare machines and use your own tests to judge a setup.