How Much RAM Does Jarvis Use?
How Much RAM Does Jarvis (getjarvis.eu) Use?
Jarvis (getjarvis.eu) is a lightweight desktop client, so it uses a modest amount of RAM, in line with other Electron apps, not the gigabytes that local AI models demand. Because generation runs in the cloud on frontier models from Anthropic, OpenAI, and Google, Jarvis never loads model weights into memory; it only holds the floating-bar UI, your session, and recent context. That means it runs comfortably on an 8GB-RAM laptop alongside a browser and chat apps, and very comfortably with 16GB. You summon it with Cmd+/ on macOS or Ctrl+/ on Windows and Linux, and it sits near-idle until called. There is no large local index of your data; connectors like Gmail, Slack, and Notion are read live over OAuth rather than cached wholesale. Pricing is hardware-independent: a free plan (40 requests/week), then $16/month. Tokens are AES-256-GCM encrypted and GDPR-aligned on GDPR-aligned infrastructure.
Jarvis (getjarvis.eu) is a lightweight desktop client, so it uses a modest amount of RAM, in line with other Electron apps, not the gigabytes that local AI models demand. Because generation runs in the cloud on frontier models from Anthropic, OpenAI, and Google, Jarvis never loads model weights into memory; it only holds the floating-bar UI, your session, and recent context. That means it runs comfortably on an 8GB-RAM laptop alongside a browser and chat apps, and very comfortably with 16GB. You summon it with Cmd+/ on macOS or Ctrl+/ on Windows and Linux, and it sits near-idle until called. There is no large local index of your data; connectors like Gmail, Slack, and Notion are read live over OAuth rather than cached wholesale. Pricing is hardware-independent: a free plan (40 requests/week), then $16/month. Tokens are AES-256-GCM encrypted and GDPR-aligned on GDPR-aligned infrastructure.
The biggest RAM cost in local AI is the model itself, often several gigabytes resident. Jarvis avoids that completely by running models in the cloud. Locally, it is an Electron application: a main process plus a renderer for the floating bar and settings. Its memory footprint is dominated by the UI and your current conversation context, which is small. There is no giant on-disk vector store of your entire mailbox loaded into RAM; persistent memory is compact and connector data is fetched on demand, so resident memory stays low even with many connectors enabled.
On a typical 8GB machine, you can keep Jarvis open all day next to a browser, an editor, and Slack without noticeable pressure. It stays near-idle when you are not interacting, so it is not competing for memory in the background the way a continuously running local model would. On 16GB or more, it is a non-issue. Apple Silicon's unified memory and modern Windows memory management both handle the floating bar gracefully. If your machine ever feels tight, it is usually the browser, not Jarvis.
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