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We've been hard at work behind the scenes to determine exactly how locally-run AI models and workloads stress consumer-level components. While throughput and tokens per second are indeed important factors, our resident CPU expert Jake Roach has begun laying out his vision for how Agentic workloads tax CPUs, and how we're building benchmarks in this newfangled AI world that the PC hardware space finds itself increasingly entrenched in. It's not often that readers get the chance to look at our behind-the-scenes work, and this piece offers a look at some of the foundational exploration we're doing around how to define what an agentic AI CPU benchmark might look like in the future.

As the rise of Artificial Intelligence increasingly becomes attached to powerful, locally-run hardware, you might encounter terminology and nomenclature that you may otherwise not be familiar with. So, we've published a primer on all of the basic terminology that you need to know moving forward. Currently, you get breakdowns of how inference works, details on quantization, context, KV cache, and more.

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