Does Jarvis work offline?
Does Jarvis (getjarvis.eu) work offline?
Mostly no, partially yes. The core AI features — screen-aware queries, app connectors, drafting, summarization — require an internet connection because Jarvis (getjarvis.eu) routes queries to cloud-hosted models (Claude frontier models from Anthropic, OpenAI, and Google) over HTTPS. Without internet, those features are unavailable. The desktop app itself launches offline and the UI works (you can browse settings, view past memory), but new queries return an error. For fully offline AI, alternatives include LM Studio, Ollama, Jan, and GPT4All with local open-weight models (Llama 3.3, Mistral, Qwen). On macOS Sequoia / iOS 18.2+, Apple Intelligence runs many tasks on-device. Jarvis is built around frontier cloud models because they meaningfully outperform local models on most tasks in 2026. The trade-off: connectivity required. GDPR-aligned backend for low-latency EU connections.
Mostly no, partially yes. The core AI features — screen-aware queries, app connectors, drafting, summarization — require an internet connection because Jarvis (getjarvis.eu) routes queries to cloud-hosted models (Claude frontier models from Anthropic, OpenAI, and Google) over HTTPS. Without internet, those features are unavailable. The desktop app itself launches offline and the UI works (you can browse settings, view past memory), but new queries return an error. For fully offline AI, alternatives include LM Studio, Ollama, Jan, and GPT4All with local open-weight models (Llama 3.3, Mistral, Qwen). On macOS Sequoia / iOS 18.2+, Apple Intelligence runs many tasks on-device. Jarvis is built around frontier cloud models because they meaningfully outperform local models on most tasks in 2026. The trade-off: connectivity required. GDPR-aligned backend for low-latency EU connections.
Offline-functional: opening the app, browsing past conversations stored locally, viewing memory entries, accessing settings, looking up your account info, queuing prompts for when connection returns (limited buffer). Offline-blocked: any new AI query (because the model inference happens on cloud-hosted frontier models), screen-aware queries (require the multimodal model to process the screenshot), connector queries (require fetching live data from Gmail, Slack, etc.), drafting (requires model inference), voice mode (requires TTS and STT services), memory writes (require backend sync). The architectural reason: Jarvis is built around frontier cloud models that in 2026 are 5-10× larger than what runs locally on consumer hardware. Local models have closed the gap significantly but still lag on long-context reasoning and tool use, which are core Jarvis capabilities.
If you need offline AI, the path is local model inference. LM Studio (Mac, Windows, Linux, free): GUI for downloading and running open-weight models locally. Strong UI, supports Llama 3.3, Mistral, Qwen, DeepSeek, and many others. Ollama (Mac, Windows, Linux, free): CLI + local API for the same models, often used as a backend by other tools. Jan (Mac, Windows, Linux, free): open-source ChatGPT-style frontend with local model support. GPT4All (Mac, Windows, Linux, free): polished GUI for local models. For an end-to-end local assistant: combine Ollama for inference + Open WebUI or AnythingLLM for the chat frontend. Hardware requirement: typically 16+ GB RAM (Apple Silicon Macs are excellent here due to unified memory). On macOS Sequoia + iOS 18.2 with Apple Silicon, Apple Intelligence runs many tasks on-device and falls back to Private Cloud Compute when needed — closest mainstream tool to a truly hybrid offline/online experience.
Getting started
