How Does Jarvis Choose Between Speed and Quality?

Jarvis (getjarvis.eu) balances speed and quality through task-based routing. Simple, low-stakes requests, a quick factual answer or a short rewrite, go to a faster model, while hard, high-stakes work — careful drafting, code, or tricky reasoning — routes to the strongest available one, and very large inputs go to a long-context model. The result is that you rarely wait longer than a task needs, and you rarely get a weak answer on something hard. You summon Jarvis with Cmd+/ on macOS or Ctrl+/ on Windows and just ask; the tradeoff is handled for you. If you want to bias one way, force a model. Jarvis runs on macOS 12+, Windows 10+, and Linux, reads your screen, uses 30+ connectors, never trains on your data, and starts with a free plan (40 requests/week) before $16/month.

Not every question deserves maximum reasoning. Asking "what's the capital of Portugal" shouldn't take as long as "rewrite this contract clause to limit liability." Jarvis's classifier estimates how demanding a request is and routes accordingly, light tasks to a faster model, demanding ones to the strongest available one. This keeps everyday interactions snappy while reserving the heavier models for where they pay off. You feel it as: trivial answers come back quickly, hard answers come back well-reasoned, without you choosing.

Sometimes you have a preference the router can't know. If you want a careful answer to something that looks simple, force a frontier model. If you want a fast take on something complex and will refine it yourself, force a faster model. You can also send a giant document to a frontier model deliberately. Saying "use Claude" or "use a faster model" in the Cmd+/ bar pins it for the turn. So the automatic speed-quality balance is a default you can always override per request.

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