alt Hacker News> Use cloud models only when they’re genuinely necessary.
The problem is that it's much easier to use the SOTA models (especially if they are subsidized) instead of spending time fixing the knobs with the local one.
I just realized this with coding agents, yeah, you probably shouldn't always use latest version at xhigh, but you will end doing it because you do the job in less time, with less "effort" and basically at the same price.
I guess we'll see a real effort for local AI only when major vendors will start billing based on actual token usage.
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The path of least resistance usually wins, especially when the pricing hides the real cost
I'm also just not seeing good performance from local models. Every time a thread about LLMs comes up, there are tons of people in the comments insisting that they're getting just as good results from the latest DeepSeek/qwen/whatever as with Opus, and that just hasn't been my experience at all: open-source models just fall over completely compared to Claude when asked to do anything remotely complicated.
I have a sneaking suspicion this is kinda like the situation with Linux in the 90s, where it kinda worked but it reeeeeally wasn't ready for the home user, but you had a lot of people who would insist to your face everything was fine, mostly for ideological reasons.
> The problem is that it's much easier to use the SOTA models (especially if they are subsidized) instead of spending time fixing the knobs with the local one.
That's not a problem, that's a feature; I have something like 8 tabs open to different free-tier providers. ChatGPT, Claude and Gemini are the SOTA ones.
I have no problem maxing one out, then moving to the next. I can do this all day, have them implement specific functions (or classes) in my code. The things is, because I actually know how to write and design software, I don't need to run an agent in a loop to produce everything in a day, I can use the web chatbots with copy/paste to literally generate thousands of lines of code per hour while still having a strong mental model of the code that I can go in and change whatever I need to.[1]
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[1] Just did that this morning on a Python project: because I designed what I needed, each generation was me prompting for a single function. So when I needed to add something this morning I didn't even bother asking an chatbot to do it, I just went ahead directly to the correct place and did it.
You can't do that if you generate the entire thing from specs.