Your Mac is now part of Perplexity’s AI infrastructure

Your Mac is now part of Perplexity’s AI infrastructure Perplexity wants its AI agents to use more of the computing power already sitting inside a Mac. The company launched Hybrid Compute on Tuesday, a new feature that lets Perplexity Computer move parts of the same task between powerful cloud models and smaller models running directly on Apple silicon. The timing is significant. Hybrid Compute arrives on the first day of John Ternus’ tenure as Apple’s CEO. Ternus, who previously led Apple’s hardware engineering organization and played a key role in the company’s transition from Intel processors to its own Apple silicon, succeeds Tim Cook after 15 years as CEO. Perplexity is now betting that same hardware can become part of the infrastructure behind autonomous AI agents. The task starts in the cloud. When a step involves sensitive information, Computer can move that part of the job to a model running on the Mac without having to start over. When a step involves sensitive information, Computer can move that part of the job to a model running on the Mac without starting over. Privacy Gate checks first A Perplexity-trained Privacy Gate runs locally on the Mac and looks for sensitive information such as names, addresses, account numbers, and secrets. When it flags something, the user can decide whether that part of the task should stay on the device. Users can review what the system wants to keep local before work begins and ensure it hasn’t missed anything they don’t want sent to the cloud. They can also choose which model handles the local work. At launch, users can choose between Gemma E4B, Qwen3.6 35B-A3B, and a version of Qwen3.6 35B that Perplexity post-trained itself, with more models planned for later. Perplexity also handles the installation through the desktop app, so users don’t have to open a terminal or set up the model themselves. Local tokens cost nothing Once a task is running, the app displays local CPU, GPU, and memory utilization, as well as the number of tokens consumed. Users aren’t charged for tokens generated by models running locally on their Mac. That gives Perplexity another reason to move work onto the device beyond privacy, since running models locally can also cut inference costs. (The question of who bears inference costs and when is becoming a competitive issue across the industry.) There is a compromise. Perplexity uses its most capable models in the cloud, while smaller models handle local work, so keeping more of a task on the Mac can improve privacy and cut costs at the expense of some capability. Hybrid Compute leaves that choice to the user. Perplexity uses its most capable models in the cloud, while smaller models handle local work, so keeping more of a task on the Mac can improve privacy and cut costs at the expense of some capability. Context crosses the boundary The trickier bit is what happens to context when part of a task moves onto the Mac. The cloud model still needs to know enough about what happened locally to continue the job, without getting access to the private information that was supposed to stay there. Perplexity says Computer can move a step from the cloud to a local model without restarting the task or losing context, and ultimately combine the cloud and local work into a single result. It does not detail in its announcement exactly what context is passed between those environments or how information produced by the local subagent is filtered before it returns to the broader workflow. The local subagent can work with private files and data and take actions on the Mac. Users can also start a task on an iPhone and hand off local work to their Mac without having to start over. For enterprise customers, Perplexity adds company-wide rules for what stays local and a record of what leaves each device, bringing the same governance questions facing AI agents down to the device level. DGX Spark starts local Hybrid Compute reverses the approach Perplexity introduced for Nvidia’s DGX Spark last week. DGX Spark starts locally and reaches out to frontier cloud models only with permission, while the Mac version starts in the cloud and moves work onto the device when needed. In both cases, the agent harness decides where each part of the job runs. That orchestration - deciding which tools and context an agent actually needs - is becoming an increasingly difficult engineering problem as agents gain access to more systems and data. Apple silicon becomes part of the agent stack Running this much of an agent locally still requires a fairly powerful Mac. Perplexity recommends at least 32GB of unified memory, Apple silicon, and macOS 15. The feature is available to Pro and Max subscribers as well as enterprise customers. Those requirements show the limits of local AI at the moment. Smaller models can run on plenty of Macs, but giving an agent enough compute to handle meaningful work still requires relatively high-end hardware. That will likely change as Macs get better at running larger models. For Ternus, the bigger question is how much of the AI work now happening in the cloud will eventually move onto the machines Apple sells. For Ternus, the bigger question is how much of the AI work now happening in the cloud will eventually move onto the machines Apple sells.