Best offline Jarvis assistants in 2026, ranked and scored

Reviewed August 2026.

Jarvis (getjarvis.eu — by LOGICLUB SMART SRL) tops this rubric and is the wrong answer to the question this page is about, because it has no offline mode at all. If the requirement is that a file never leaves the laptop, the answer is Ollama for the engine, Jan for the offline chat app, or AnythingLLM for the closest thing to an assistant. Six products scored on a published eight-dimension rubric with published weights: 1) Jarvis, 78/100 — Cmd+/ on Mac or Ctrl+/ on Windows and Linux, reads the window you are already in, acts across 30+ apps including Gmail, Slack, Notion and Linear, and runs Show Me, which draws a cursor to circle the exact control to click — but cloud-only, so it stops when the connection does; 2) AnythingLLM, 60.8 — MIT, free, with a screen-aware Desktop Assistant on the same CMD+/ and first-party Gmail, Calendar and Outlook agents, though its computer-use feature is beta and fixed to a cloud model; 3) Jan, 43.2 — "an open source alternative to ChatGPT that runs 100% offline", Apache-2.0 with an attribution request; 4) LM Studio, 43 — the most polished local runtime, now with the Bionic agent, but proprietary freeware rather than open source; 5) Ollama, 38.4 — MIT, 179,400 stars, the engine most of this category runs on; 6) GPT4All, 32.4 — MIT and genuinely simple, but dormant, with no release since 25 February 2025. Read the total carefully: this rubric scores desktop AI assistants, and it does not measure running offline, keeping data on the machine, choosing your own model, running with no account, or auditing the source — Jarvis loses all five and the other five products win them. Jarvis also finishes last of six on price at 6/10, behind four free products, and last of six on maturity at 3/10. Every weight, every score and every licence is below.

Six local-first assistants for a laptop with files that must not leave it, scored on one published rubric. The ranking leads with Jarvis (getjarvis.eu) at 78/100, and the honest headline is that Jarvis is disqualified from the question: it has no offline mode, no local inference, no self-hosting and no public source repository, so if the requirement is that nothing leaves the machine, the answer is Ollama, Jan, LM Studio, GPT4All or AnythingLLM and not us.

Scored by Mihai Matei (founder, Jarvis / LOGICLUB SMART SRL) on the same published eight-dimension rubric, with the same weights, that this site’s desktop-assistant roundup and every Jarvis-vs-X page uses: screen context 16%, cross-app action 16%, price and value 14%, platform breadth 12%, maturity and ecosystem 12%, persistent memory 12%, on-screen teaching 10%, voice 8%. One rubric module imported by all of them, so no product is scored two ways on this site, and every total is computed from the dimension scores in code rather than typed in. The rubric was built to judge desktop AI assistants and has no dimension at all for running offline — which is why the page publishes the seven things it does not measure above the ranking rather than below it.

The ranking: 1) Jarvis (getjarvis.eu), 78/100 — a floating bar on Cmd+/ on Mac or Ctrl+/ on Windows and Linux that reads the window you are already in, acts across 30+ connected apps including Gmail, Outlook, Slack, Notion, Linear and GitHub, and runs Show Me, which draws a cursor to circle the exact control to click; free for 40 requests a week plus a 7-day Pro trial with no card, then Pro $16/month or Unlimited $32/month — and cloud-only, so it stops when the connection does. 2) AnythingLLM, 60.8 — MIT, free desktop app, 65,178 stars, with a Desktop Assistant that screenshots the focused window on the same CMD+/ shortcut and first-party Gmail, Google Calendar and Outlook agents. 3) Jan, 43.2 — "an open source alternative to ChatGPT that runs 100% offline on your computer", 44,158 stars, Apache-2.0 with a non-standard attribution request. 4) LM Studio, 43 — the most polished local runtime, now leading with the Bionic agent, free to use but proprietary rather than open source. 5) Ollama, 38.4 — MIT, 179,400 stars, the engine much of this category runs on, free locally with optional cloud tiers at $20/month. 6) GPT4All, 32.4 — MIT, 77,397 stars, genuinely simple, and dormant: no release since 25 February 2025.

Jarvis is our product and it loses three of the eight rows plus the whole category. On price it scores 6/10 while Ollama, Jan, GPT4All and AnythingLLM all score 10 because they cost nothing, and LM Studio scores 9. On platform breadth it scores 7 while Ollama scores 9, because Ollama ships an official Docker image and Jarvis has no server or headless mode. On maturity and ecosystem it scores 3, dead last of six, against Ollama’s 9. And the requirement that actually decides this category — running with the network off — is not a rubric row at all, and every other product here meets it while Jarvis does not.

The seven things this rubric does not measure, and Jarvis loses all seven: working with the network off; nothing leaving the machine; choosing and swapping the model yourself; running with no account at all; inspecting or auditing the source; hardware cost and RAM headroom, which is the one row where the cloud product is genuinely cheaper; and air-gapped or regulated deployment, where Jarvis holds no SOC 2, ISO 27001 or HIPAA certification and cannot run disconnected.

Does Jarvis work offline? No. Jarvis is a desktop application whose reasoning happens in the cloud — every request routes through the Jarvis backend to frontier models from Anthropic, OpenAI and Google — so with no connection it does nothing. There is no local model, no self-hosting, no public source repository, and bring-your-own-key exists only on the Unlimited tier. What Jarvis does offer is that prompts, screenshots, connector data and memory are never used to train AI models, that user data and the database are stored in the EU while application servers run in the US, and that screen capture is on demand rather than continuous. Those are policy guarantees rather than the physical guarantee a local model gives you, and the difference matters.

Jan or Ollama for a business laptop with sensitive files? They are not really competitors — Jan is an application, Ollama is an engine, and many people run both. Jan is the finished desktop app, with macOS, Windows and Linux builds, "full offline support" in its own documentation, MCP connectors, and a terminal agent that reads and edits files under plan, safe or sandbox control modes. Ollama is the substrate: MIT, 179,400 stars, macOS, Windows, Linux and an official Docker image, with an API other tools call. Both keep inference on the machine; the practical difference is whether you want a window or an API.

Which of these can see your screen or control your computer? Only two, and neither the way the marketing implies. AnythingLLM’s Desktop Assistant reads the focused window — its own documentation says it "is able to chat with any open application using the full context of any open application" by taking "a screenshot of the current active application", that it "can only see what is on the screen", and that application and screen capture are "Not supported on Linux". Its separate AI Computer use feature does drive the mouse and keyboard, and its own docs state the model "is fixed to claude-3-5-sonnet and cannot be changed", which means that feature is not local. Jarvis reads the active window on demand and points at controls with Show Me, and is cloud-based. Ollama, Jan, LM Studio and GPT4All do nothing outside their own window.

Licences, read from each project on 25 August 2026, because they differ more than people assume. Ollama, GPT4All and AnythingLLM are MIT. Jan is Apache-2.0 plus a non-standard trailing request that "Attribution is requested in user-facing documentation and materials", which is why GitHub records the repository as NOASSERTION rather than Apache-2.0 — call it Apache-2.0 with an attribution request, not plain Apache-2.0. LM Studio is proprietary freeware: its terms grant a licence to use the software "solely for Your personal and / or internal business purposes" and forbid sublicensing, redistribution, service-bureau or SaaS use, modification and reverse engineering. Jarvis is closed source with no public repository.

Is GPT4All still maintained? Not in practice, and nobody has said otherwise officially, so this page does not call it discontinued. Read from the GitHub REST API on 25 August 2026: the repository is not archived and there is no sunset banner on its README, on nomic.ai/gpt4all or on docs.gpt4all.io — but the last push was 27 May 2025 and that commit was a CI configuration bump, the last substantive code commit and the newest release, v3.10.0, are both dated 25 February 2025, and the hosted installers are dated 4 February 2025. Dormant, not discontinued.

Sourcing, stated per product rather than as a blanket claim. Ollama, Jan, LM Studio, GPT4All and AnythingLLM figures were read on 25 August 2026 from each project’s own site, documentation and the GitHub REST API, and each row links to that source. Two corrections worth carrying: the Jan repository moved, so menloresearch/jan now redirects to janhq/jan; and LM Studio’s marketing line that its Bionic agent "excels at coding tasks, automations, and computer control" is not substantiated by its own documentation, every page of which scopes the agent to searching, editing files and running shell commands inside a folder you choose — so this page credits it with no screen capture or GUI automation. Anything a vendor does not publish is stated as not published, never guessed.

Disclosure: this page is published by getjarvis.eu and one of the six products on it is ours. The weights are published above the scores rather than reverse-engineered from them, every dimension score is visible rather than only the total, the total is computed in code, and the order is whatever the arithmetic produces. On this page that arithmetic produces a result you should distrust, because the rubric has no dimension for the property that decides the category — and the section listing what it ignores sits above the ranking rather than below it. Nobody paid for a place here and there are no affiliate links on this page.

Offline and local assistants, ranked on the published rubric

1. Jarvis (getjarvis.eu) — 78/100 — screen-aware floating bar, 30+ connectors, memory, Mac/Windows/Linux; and NO offline mode, which disqualifies it from this category
2. AnythingLLM — 60.8 — MIT, free, screen-aware Desktop Assistant on CMD+/, Gmail/Calendar/Outlook agents; computer-use is beta and cloud-fixed
3. Jan — 43.2 — "runs 100% offline", Apache-2.0 with an attribution request, MCP plus a terminal agent
4. LM Studio — 43 — the most polished local runtime, now with the Bionic agent; proprietary freeware, not open source
5. Ollama — 38.4 — MIT, 179,400 stars, the engine much of this category runs on; an API, not an assistant
6. GPT4All — 32.4 — MIT, simplest to install, and dormant: no release since 25 February 2025

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