Does Jarvis Remember Context When It Changes Models?

Yes. When Jarvis (getjarvis.eu) routes different turns to different models — say a vision question to one model and a follow-up rewrite to another — it carries the conversation and your on-screen context across, so switching models does not reset the thread. Jarvis also has persistent, user-controlled memory, so relevant facts you have established can persist across sessions, not just within one. You interact through the same floating bar (Cmd+/ on macOS, Ctrl+/ on Windows) the whole time; the model behind each answer can change without you losing continuity. This means a multi-step task stays coherent even though frontier models from Anthropic, OpenAI, and Google may each handle a step. Memory is yours to view and control. It is all in the $16/month Pro plan (Unlimited $32/month) with a free plan (40 requests/week), GDPR-aligned with your data stored in the EU, and never used to train the models.

A fair concern with per-task routing is whether handing the next turn to a different model loses what came before. Jarvis manages this by keeping the conversation history and the current on-screen context with the session, then supplying what the next model needs to continue. So when a chat moves from a screenshot question to a code task to a draft — potentially touching different engines — each step picks up where the last left off. From your side it is seamless: one continuous thread in the bar you opened with Cmd+/ or Ctrl+/, regardless of which model answered which turn.

Beyond a single session, Jarvis has persistent memory that you control. Facts and preferences you want it to remember can carry across sessions, so you do not re-explain your context every time, and this memory is independent of which model handles a given request. Because it is user-controlled, you can see and manage what Jarvis retains rather than it silently hoarding everything. That combination — session continuity plus durable, governed memory — is what lets the multi-model design feel like one assistant with a memory rather than three forgetful ones.

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