15 pointsby m0rde4 hours ago9 comments
  • bigbadfeline2 hours ago
    > No, local models will not win

    Win what? Money, fame? That's not the point of small models, freedom is the point. What's this occultist obsession with "There shall be only one" monopolies? Why only one? That's so irrational and childish.

    • nailer2 hours ago
      Win as the dominant for of LLM interaction.

      Every so often someone hypes local models as "Don't pay for Claude check out this local modal" and the local modal isn't at all equivalent.

      That doesn't mean that local models are going anytwhere (as the article motes they're useful) but if you want the best we're stuck with expensive remote models right now.

  • yellowapple2 hours ago
    > For the setup price alone of a low-end home lab1, you could buy several years of a paid subscription to one of the AI providers. The power costs would come out to around $50-$300 per month, depending on how much inference you’re running: again, the price of a couple more paid subscriptions.

    Okay, but I already have multiple computers capable of running local models with acceptable performance, so for me the cost is $0. I suspect that's true for most people of sufficient technical inclination to be interested in and capable of running models on their local machines.

    Also, no, the monthly electricity price of even my power-hungriest machines ain't anywhere close to that figure. Hell, at the high end that's more than my power bill for my whole household.

    • robotresearcheran hour ago
      Let’s put numbers on it.

      The mean price of electricity for me is about 40c per kWh: about as high as anywhere in the US.

      There are about 730 hours in a month, and a consumer machine can sustain maybe 500W, so we can spend 0.4 * 0.5 * 730 = 146 dollars on compute power per box unless we start buying special stuff.

      • nozzlegear28 minutes ago
        For my area (nw Iowa) where electricity is about 10¢ per kWh, that'd be like $43.8 ish? In reality much less for me personally with a Mac Studio, since it doesn't go anywhere near 500W
  • qudat3 hours ago
    > Or maybe models get so good that a 30B model is genuinely smart enough to do everything, so nobody really needs a model like Opus or Sol unless they’re trying to solve the Reimann Hypothesis. I don’t really buy this. Models can do frontier mathematical work today while still being not smart enough to refactor large codebases as well as me, so it’s hard to imagine a world where I don’t just want to use the smartest model available.

    Idk, I already don’t bother with Opus and stick with sonnet med. I really care more about speed. I use qwen3.6 27b for personal projects and I think it works pretty great.

    So like the article mentions, if scaling stalls and small models get better it’s not impossible to imagine a convergence and hardware costs drop.

    Having said that, self hosting will be a niche thing like it is today for other services.

  • yunwal3 hours ago
    I think local models will not be “niche” in the future in the same way personal computers are not “niche” just because most computing happens in the cloud. They have entirely different uses
  • vivzkestrel2 hours ago
    - not if apple m6 mac studio comes with 1TB of RAM and 144 core cpu / gpu
  • Kim_Bruning3 hours ago
    Is this the old mini vs micro argument again?
  • spottedmarley2 hours ago
    Most of my inference already happens locally, actually.
  • darepublic3 hours ago
    What about that edge computing. Those cheap drones
  • cyanydeez3 hours ago
    If they dont the gap between rich and poor will be unsustainable.