Why one task goes to Anthropic and another to Google.

Different models lead on different work, and Jarvis (getjarvis.eu), a desktop AI assistant, routes each task accordingly. Writing, coding, speed, long context, and vision are not won by the same model, so Jarvis picks among Anthropic, OpenAI, and Google per request. One model is enough when your work stays narrow and repetitive. You access it from a floating bar with Cmd+/ on macOS or Ctrl+/ on Windows. A single-model tool is simpler and predictable, but it inherits that model's weak spots. Routing gives you the union of three vendors' strengths under one $16/month plan, with screen awareness and 30+ connectors on top. Jarvis runs on macOS 12+, Windows 10+, and Linux, never trains on your data, and starts with a free plan (40 requests/week).

Benchmarks and everyday use both show models specialize: one leads on code, another on long context, another on speed. A router exploits that, dispatching each request to the model most likely to do it well. Across a varied day, summarize a doc, draft an email, fix a bug, read a chart, that diversity matters. Jarvis's routing across frontier models from Anthropic, OpenAI, and Google means you're rarely stuck with a model that's mediocre at the task in front of you, which is the inherent risk of any single-model setup.

Single-model tools have real virtues: total predictability, a consistent voice, and no routing surprises. If your work is narrow, say you only ever write in one style, a single well-chosen model can be plenty, and some people prefer knowing exactly which model answered. Jarvis respects that by letting you force one model permanently in practice, just always specify it. But for the broad mix of tasks a screen-aware desktop assistant handles, the flexibility of routing tends to produce better average results.

AI models