Perplexity Brings Local Agent Runtime to AMD Ryzen AI Max PCs
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- x.com
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Portable Computer for Windows is now available on @AMD Ryzen AI Max Series processors. It makes it easy to run local AI agents that work with your connected apps and local files. Kick off tasks or schedule recurring work that runs entirely on your device.
Context
Perplexity's Portable Computer is the local version of its Computer : the , orchestrator, and a 27-billion-parameter model all run on the user's own PC instead of in Perplexity's cloud. Its Windows version first shipped for PCs with Nvidia RTX graphics, as Nvidia described in September. This announcement adds Windows machines built on AMD's Ryzen AI Max Series processors.
AMD's announcement gives the reason these chips qualify: Ryzen AI Max processors combine CPU and GPU performance with a large pool of shared memory, which AMD says lets them run local models alongside everyday applications. Perplexity's product page sets the bar at 24GB of VRAM or more, the same threshold it uses for RTX cards, and lists AMD support for Windows only; its Linux instructions cover Nvidia hardware. On a Windows PC, the page has users set up Perplexity's own PPLX 27B for local (it lists Qwen 3.8 27B as a second option on Nvidia's DGX Spark), and only one local model runs at a time. The product is available to Pro and Max subscribers.
The post says scheduled work runs "entirely on your device", and Perplexity's product page describes that as the default rather than a hard boundary. When a step needs the web or stronger reasoning than the local model offers, the orchestrator asks for approval before routing that step to one of more than 15 cloud models, then returns the result to the local run. Connected apps such as Gmail, Slack and GitHub also go through the local orchestrator. AMD and Perplexity both point to cost: work done by the local model does not use Perplexity Computer credits and carries no per-token charge, which Perplexity says makes large, repetitive jobs practical on hardware the user already owns.
- AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
- agent harness — The scaffolding around a model that turns it into a working agent — the loop, the tools it can call, and the rules for when to stop.
- sandbox — An isolated environment where AI-generated code or agent actions run without being able to touch anything real.
- inference — Running a trained model to get answers — the phase where AI is actually used, as opposed to trained.
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