Birbla

Join the discussion

Write your take first — we'll ask for email only when you're ready to publish.

Sign in
  • Hacker News
  • I’ve been wanting to get better acquainted with local inference but I don’t have the hardware, which has made me think about something I haven’t seen discussed, which is local collaboratives. The economics makes it seem like a group of people joining together to run good hardware and an open model might make sense, but I haven’t seen anything like this mentioned. Have I been missing it?

    I think it would be pretty neat to launch a service helping people who wanted to participate in something like that locate one another.

    by bnj
  • Have you read about Opencode Go? They are great provider for open model, like GLM 5.2, Deepseek v4 Pro, Kimi 2.7 Code. You should give it shot to them :-)
    by radhitya
  • Sure. But OpenAI is the same price. Why would I pay $18/month for z.ai when OpenAI is $20/month?
    by pkulak
  • Claude started becoming useful for my coding purposes after it hit version 4.6. After that sure some nice to have additions but I think if I had 4.6 sonnet & opus as open weights, I would not need something more.

    Having played a bit with Fable, reinforced the above.

    by whatever1
  • What's amazing about these models is they are effectively a distillation of the internet in something that can fit onto your local machine [1] and be queried via natural language.

    [1] It seems inevitable that decent local models will be possible as the technology and the hardware is improving at a rate beyond the growth of the knowledge base to be distilled.

    by DrScientist
  • The headline says one thing, then the article text says this:

    > I’m hoping it’s going to be minimal.

    I have multiple subscriptions and I pay per token to try out different LLM providers through OpenRouter. I also run open weight models locally.

    I just can’t agree yet. The models from Anthropic and OpenAI really are that much better than anything else. The open weight models must be universally benchmaxxed across the board because my real world experience with them is very different than what the benchmarks imply. I get downvoted a lot for speaking about my experience because I don’t think it’s the reality that people want to hear right now, but it’s true for complex work.

    I do think there are a lot of easier tasks that can be handled appropriately by the open weight models in the hands of a skilled operator. If an entire job is simple enough that you wouldn’t hesitate to hand it off to a junior with a little supervision then any model will do. However for a lot of the work I do, even Opus 4.8 on Max requires a lot of attention and extra steering and review to keep it on track. Fable did, too, though to a lesser degree. When I try to use the big open weight models (hosted, because they’re not running at reasonable speeds locally at a quantization I can tolerate) it feels like I spend more time waiting while they burn tokens for output that I probably have to reject anyway, at least for the bigger tasks. I wish they were there, but that’s not the case yet.

    by Aurornis
  • I find the attitude shown in this post very surprising. On the one hand, the post starts with a story of adopting Linux and other FOSS. The core of FOSS is giving its users the ability to understand and modify software they run. On the other hand, the rest of the post is about using a tool (LLM) that the author has no way to modify and no way to understand. Huge matrices of floats are at best comparable to compiled code. But the reality is even worse - it’s actually easier to decompile and understand proprietary software. Not to mention the fact the most of the time users can’t even run the “open” models since it requires hardware that most can’t afford.

    How did we get from prising software freedoms to this?

    by tumdum_
  • I think it's interesting that people write off open weight models because they're "a few months behind" proprietary models.

    I know LLMs move at the speed of light (especially these past few quarters), but if Opus and GPT "a few months ago" were really like open weight models, then there's really no reason to not switch, especially for those who were using these models a few months ago.

    Your codebase didn't change, so use the open weight model. Don't move the goalposts.

    by julianlam

Explore Birbla archives