Hi all,

I want to spin up a small home server. Nothing crazy, maybe 4 or 8GB ram at most. 1 Docker instance running a few privacy frontends (Invidious, Redlib, Xcancel, SearxNG, etc.) and split tunneling VPN connections for each one.

Obviously, a Raspberry Pi 4 or higher is the internet’s favorite choice, but I don’t need wireless connectivity, I just need a single HDMI and 2 USB ports to get everything set up, one ethernet port, and a dream in my heart.

Has anyone use alternatives like Le Potato or Orange Pi? I’m curious what their community support is like, and if there’s a FOSS-friendly standard.

Thanks!

  • SuspiciousCarrot78@aussie.zoneEnglish
    1·
    51 minutes ago

    I have a RPI 4b and 3 lenovos (m93p, m710q, p330).

    You can’t beat the RPI for power draw (~2w idle and ~7w under max load) but I suspect if you wanted to look at $ to utility measure you’d probably prefer the Lenovo M93P. $50 USD. Mine has i7-4785t, 16GB ddr3 (2x8iirc?) with ethernet, USB etc. Bought 2023/4. I expect base model is still that price now (mines upgraded). The only caveat is that it doesn’t have HDMI, it has display port out, but that’s just a $5 dongle or SSH issue. M73 would be a touch cheaper.

    Iirc the TDP is 35w max and can be lowered / undervolted a touch (don’t update the BIOS - it blocks throtlestop).

    I turned mine into a retro PC slash game server for the kids (luanti etc). But the siren call of doing truly impossible things with the RPI is too beguiling :)

    Eg: running diet pi (headless) with all of my services (media stack, privacy, docs, search, images etc) takes about 300 megabytes (or 650mb if I have to boot into xfce).

    300mb, 2-3w.

    That shouldn’t be possible. I love it.

    My next goal is to create an expert system / pseudo llm that sources answers based on user provided markdown or PDF, ZIM files and 4get search or Tavily.

    The advantage here is that 1) speed will be stupid fast as no neural network crap (outside of optional extra Markov chain garnish) 2) not stochastic (but allow for llm as optional “plug in module” - pi might actually run a 135M at non glacial speeds) 3) still serves openAI compat endpoint.