You can now run pplx-decider-flash-v1.2 locally on your Mac, without an API key.
Decider for Mac is an app that runs the 4B decision model on device. Ask a question about text or an image and get a probability back, all on your machine.
pplx.ai/decider-for-mac
Decider for Mac is an app that runs the 4B decision model on device. Ask a question about text or an image and get a probability back, all on your machine.
pplx.ai/decider-for-mac
Oct 22, 2026 · 10:42 PM UTC
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@perplexitydevs this sounds kinda cool, ngl. might have to check it out on my Mac. 👀
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@perplexitydevs @_duyet Would love to test and see how this compares to Jev
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@perplexitydevs Running SI locally without API keys is a big win for privacy and accessibility.
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@perplexitydevs Local with no API key is what gets me. I've been moving more of my stuff off cloud models anyway, and a 4B model that just gives me a probability back is perfect for my agents to decide when something actually needs a bigger model.
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@perplexitydevs The screenshot example makes this click for me. I'd start with a contact sheet of suggested groups before moving files, so one odd category doesn't turn into a scavenger hunt.
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The Software Industry is Abandoning Peer Review
AI is Building its Own Sandbox Without Human Oversight
bradcorlett88.substack.com/p/the-software…
AI is Building its Own Sandbox Without Human Oversight
bradcorlett88.substack.com/p/the-software…
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@perplexitydevs Love the zero API key setup, though my 256GB Mac SSD always feels those 5.8GB weight downloads.
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@perplexitydevs @perplexity_ai Good stuff
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@perplexitydevs @perplexity_ai And now you do what they told ya
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@perplexitydevs can it pick a restaurant before everyone starts saying "anything is fine"?
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@perplexitydevs the pre-commit check is the use i'd try first. is the probability calibrated, like does 0.7 mean it's right about 70% of the time on your evals? that decides whether i can pick one threshold and trust it or have to tune it per question
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@perplexitydevs A decision model earns its place when the routing call costs less than the call it replaces. Keep the classifier's job narrow — binary yes/no with a probability — and send the big model everything below the confidence threshold. On-device: no queue, no data leaving the machine.
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