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Posted by sbochins 8 hours ago

AI coding at home without going broke(stephen.bochinski.dev)
215 points | 195 commentspage 5
jrm4 7 hours ago|
Is spending (metered money) even worth it? Perhaps for most I mean "beyond like a 30 bucks a month," but for me I'm literally not spending more money beyond my very cheapo 16gb video card.

No clue what y'all are doing, perhaps because I'm hobbying, and also I'm old and can perhaps do more of this by hand.

But I'm basically just doing what I did before, plus ollama self hosted and sometimes gemini and I feel like I'm going lightspeed beyond what I've ever done.

And I suppose this is still very fine-grained. I have it make a draft, then just have them fix/change it step by step?

I tried one of the bigger boys that can one-shot apps, which I guess is cool, but I'm finding it's just as hard to modify as if I just grabbed someone elses repo on github.

stkdump 5 hours ago|
No, I have the same experience. Feels crazy that a GPU is too expensive and then the advice is to spend 400$+tokens on openrouter each month.
sesm 7 hours ago||
> Do that well and you can build what a team of twenty engineers would put out in a month for around a thousand dollars.

As usual, an extraordinary claim without an extraordinary evidence: https://stephen.bochinski.dev/apps/

tamimio 7 hours ago||
You can have opencode and switch between multiple providers based on the tasks you are doing on the fly, normal tasks use deepseek for example, hard one use gpt5 or opus4, and track the usage with something like codexbar or similar. Openrouter seems to charge extra on top of the api costs, same with zen ide, so keep that in mind.
gaigalas 8 hours ago||
> The first is to self host. You buy the machine, run open source models locally, and pay nothing per token after that.

In the good ol' days, we bought machines not only to run stuff, but to experiment.

I understand today experiments are limited. Inference is reasonable, fine-tuning is either niche or a stretch, and base training is impossible.

*That is bound to change*, and when it does, there will be an avalanche of hobbysts and amateurs poking at base training. They'll find optimizations no one found before, synthetize data no one ever imagined to synthetize, and when that happens we'll start getting libre models.

So, yeah. Right now, buying the machine doesn't pay off that well, unless you want to pioneer this stuff in severe adverse conditions (hardware prices inflated, etc). Eventually, it will.

zuzululu 8 hours ago||
Another update for codex users they let you accumulate resets which greatly adds to the mileage

I don't think its feasible to have something comparable to these frontier models when they are increasing usage and lowering token costs

verdyshd 1 hour ago||
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hottrends 2 hours ago||
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knightops_dev 4 hours ago||
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KaiShips 6 hours ago||
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aplomb1026 7 hours ago|
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