--- title: "Unplug the Internet and Use It — What People Who Installed Jan Brag About and Complain About" date: 2026-10-10 model: qwen3.6-plus author_type: human category: reviews summary: Jan is a desktop AI that runs offline, and that one sentence makes it easy to recommend installing. Actual users don't deny that advantage. But measured token speed slower than Ollama on the same hardware, the confusion of picking the wrong model, and the feel on a CPU-only system keep showing up. Here's where the bragging and the complaining diverge. tags: Jan,local AI,offline AI,Ollama,Tauri,GGUF,local LLM,desktop app,user reviews,real user reviews --- # Unplug the Internet and Use It — What People Who Installed Jan Brag About and Complain About "On the plane, on flaky hotel wifi, Jan just works." A multi-month review posted in March 2026 described Jan's biggest advantage that way. On the other side, in February 2026, r/LocalLLaMA carried a post titled "New computer arrived... JAN is still super slow." Its author had turned on the latest Jan on a new laptop with 64GB of RAM and an RTX PRO 2000, and wrote that at most one word came out per second and the GPU didn't seem to be used at all. The emotional gap around Jan isn't a lack of performance — it's **what kind of feeling you get under what conditions.** This post translates the bragging and the complaining, each with its basis. --- ### 1. Scope of sources I read two independent measurement blogs (2026-03, 2026-06), r/LocalLLaMA user posts (2025-06 through 2026-02), and Jan's official docs and announcements. The token speed figures are those blogs' own measurements; a different environment gives different results. --- ### 2. The brag — offline, simple install, the Tauri move Three things the positive side names in common. **First, completely offline.** Once you download a model, chat works with no internet. A March 2026 review wrote: "used it on the plane, and I was more grateful than I expected." One condition attached: only for models you've already downloaded. He said he watched a user fail trying to get a new model while on a plane. **Second, polish as a desktop app.** A June 2025 r/LocalLLaMA post welcomed the v0.6.0 update. Moving from Electron to Tauri and getting lighter, custom assistants, and themes were all praised. A comment carried a positive report: "about 35 t/s on a 4060 for Jan-nano, and MCP worked well too." **Third, versatility.** Supporting Mac, Windows, and Linux, plus providing an OpenAI-compatible local API server so you can attach other tools — this comes up repeatedly. --- ### 3. The complaint — same hardware, slower speed The core of the complaint isn't model quality — it's the **relative inferiority in inference speed.** A June 2026 independent measurement blog compared Jan and Ollama using the same Gemma-family model. First measurement: Ollama 6.62 t/s, Jan about 5 t/s. Second: Ollama 7.35 t/s, Jan 3 t/s. That's a difference on the same device. The author added the caveat that "on systems with a GPU it may differ greatly." The same post actually included an estimate of rising to 13 to 15 t/s on Radeon, Arc, and 4050 hardware. The second problem that same post recorded is system freeze. He said he'd had the whole system come to a stop with a Gemma-family model, and wrote: "I didn't hit a similar problem on Ollama." The complaints continue on new hardware too. The author of that February 2026 post ran a Devstral-Small GGUF with GPU acceleration switched on and still got about one word per second. The comments' diagnosis is consistent: GPU VRAM is only 8GB, so the model is spilling over to the CPU, and the advice is that a MoE-family model with fewer active parameters does better in that situation. --- ### 4. The fork — model size is the whole game The third axis is the **model size** the user picked. The March 2026 review wrote that on a 13B model "the fan made an airplane engine noise with every response," and recommended starting from 7B or 8B. His summary method: if a short paragraph takes over thirty seconds, the model is too big for the machine. Don't wait for the larger model — step down one. The combo he settled on was "one small model for fast drafts, one mid-size model for work you can wait on." How the same user divided Jan and Claude's roles runs on the same principle. Sensitive content, offline, no-subscription draft work goes to Jan. Long context, careful reasoning, and fast round-trips go to the cloud. The summary sentence: "when I treated the two as competitors, Jan felt disappointing." One more failure case worth noting. In a January-v1 small-model test from August 2025, the search tool (Brave) missed all three times, and the same search getting stuck in a loop was observed twice. The Jan developer showed up in the thread and answered: "4B models drop performance significantly at Q4 quantization. I recommend Q8. Jan Hub defaulting to Q4 — we'll improve that." That reply remains in the thread. --- ### 5. Conclusion — the price of offline The user evaluation of Jan sorts into this structure: - **The advantage is structural.** Offline, free, cross-platform, a lightweight Tauri-based app. Almost no rebuttal on this part. - **The complaint is conditional.** It appears when CPU-only, VRAM overflow, or oversized model selection attach as conditions. - **The fix is simple.** Start with the smallest model your machine can handle and secure the speed first. The answer users left to "is Jan slow" reads like this: **what's slow isn't Jan — it's that laptop's RAM and the model you chose.** And what Jan gives a person willing to tolerate that feeling — a private assistant in a corner of an airplane — is something no other tool substitutes for. Related posts: [GPT4All user reviews](/reviews/2026-10-10-gpt4all-rag-user-reviews/) · [llamafile user reviews](/reviews/2026-10-10-llamafile-single-file-user-reviews/) · [Jan agent hub entry](/agents/jan/) --- ### Sources - Speed and freeze measurements: [I Tried This Open Source ChatGPT Alternative on Linux, But Went Back to Ollama (It's FOSS, 2026-06)](https://itsfoss.com/jan-ai/) - Multi-month review: [I've Been Using Jan as My Free Local AI — Honest Review After Several Months (2026-03)](https://sinhaabhinav.in/blog/jan-ai-review-2026) - Slow-down testimony: [New computer arrived... JAN is still super slow. (r/LocalLLaMA, 2026-02)](https://www.reddit.com/r/LocalLLaMA/comments/1qzaps9/new_computer_arrived_jan_is_still_super_slow/) · [I tried the Jan-v1 model released today (2025-08)](https://www.reddit.com/r/LocalLLaMA/comments/1mov3d9/i_tried_the_janv1_model_released_today_and_here/) - Tauri update: [Jan got an upgrade: New design, switched from Electron to Tauri (2025-06)](https://www.reddit.com/r/LocalLLaMA/comments/1lf5yog/jan_got_an_upgrade_new_design_switched_from/)