How Is Jarvis Memory Different From ChatGPT Memory?

Jarvis (getjarvis.eu) memory works everywhere on your desktop, while ChatGPT memory only works inside ChatGPT. Because Jarvis is a screen-aware floating bar (Cmd+/ on macOS, Ctrl+/ on Windows) wired to 30+ apps, a remembered preference like 'keep emails short' applies in Gmail, Slack, and Notion alike — not just in one chat window. Jarvis also routes across frontier models from Anthropic, OpenAI, and Google rather than a single model, supports per-project scoped memory, and is GDPR-aligned with GDPR and EU AI Act alignment. Crucially, Jarvis never trains on your data, whereas you have to opt out of training in some other assistants. Both let you inspect and delete memories. Jarvis is free to start, then $16/month for Pro.

The biggest difference is where memory applies. ChatGPT's memory helps when you're chatting with ChatGPT. Jarvis lives at the OS level as a floating bar and sees your screen, so its memory follows you into every app and across 30+ connectors. Tell Jarvis your sign-off once and it uses it whether you're in Outlook, Slack, or Google Docs. That makes Jarvis feel less like a chatbot that happens to remember you and more like an assistant embedded in your actual workflow.

Jarvis adds structure ChatGPT's memory doesn't emphasize. It supports per-project scoped memory, so a client's conventions stay separate from another's, and global facts apply everywhere. And because Jarvis routes per task across frontier models from Anthropic, OpenAI, and Google, your remembered context informs whichever model best fits the job — a long-document task might use a faster model while a nuanced draft uses the strongest available one. You're not locked to a single provider's model or a single global memory bucket.

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Memory & context