I'm currently making an effort to switch to local for stuff that can be local - initially stand alone tasks, longer term a nice harness for mixing. One example would be OCR/image description - I have hooks from dired to throw an image to local translategemma 27b which extracts the text, translates it to english, as necessary, adds a picture description, and - if it feels like - extra context. Works perfectly fine on my macbook.
Another example would be generating documentation - local qwen3 coder with a 256k context window does a great job at going through a codebase to check what is and isn't documented, and prepare a draft. I still replace pretty much all of the text - but it's good at collecting the technical details.
> Smart Cloud Routing > > Large-context requests auto-route to a cloud LLM (GPT-5, Claude, etc.) when local prefill would be slow. Routing based on new tokens after cache hit. --cloud-model openai/gpt-5 --cloud-threshold 20000
Edit: I’d also consider waiting for WWDC, they are supposed to be launching the new Mac Studio, an even if you don’t get it, you might be able to snag older models for cheaper
They have a metric called Model-Harness Index:
MHI = 0.50 × ToolCalling + 0.30 × HumanEval + 0.20 × MMLU (scale 0-100)
I understand why they have to charge more, but not many are gonna be able to afford even $100 a month, and that doesn't seem to be sufficient.
It has to come with some combination of better algorithms or better hardware.
Who’s wrong?
Google when they merged YouTube and Google+, Reddit multiple times, Facebook after countless scandals. Microsoft destroying windows and pushing ads.
At the end of the day a solid product and company can withstand online controversy.
Not that they don't bring value, I'm just not convinced they'll be able to sell their products in a sticky enough way to make up the prices they'll have to extract to make up for the absurd costs.
I'd agree with you, except I've heard this argument before. Amazon, Google, Facebook all burned lots of cash, and folks were convinced they would fail.
On the other hand plenty burned cash and did fail. So could go either way.
I expect, once the market consolidates to 2 big engines, they'll make bonkers money. There will be winners and losers. But I can't tell you which is which yet.
Unless you compare with the reported cash burn or projected losses.
> they’ll raise effective prices some more while Claude diffuses into the economy, sounds like a money printer
But the problem is, they have no moat. Even if Claude diffuses into the economy (still to be seen how much it can effectively penetrate sectors other than engineering, spam, marketing/communications), there is no moat, all providers are interchangeable. If Antrhopic raise the prices too much, switch out to the OpenAI equivalent products.
I disagree very strongly with this, both anecdotally and in the data - subscriptions are growing in all frontier providers; anecdata is right here in HN when you look around almost everyone is talking about CC, codex is a distant second, and completely anecdotally I personally strictly prefer GPT 5.3+ models for backend work and Opus for frontend; Gemini reviews everything that touches concurrency or SQL and finds issues the other models miss.
My general opinion is that models cannot be replaceable, because a model which can replace every other provider must excel at everything all specialist models excel at and that is impossible to serve at scale economically. IOW everyone will have at least two subscriptions to different frontier labs and more likely three.
If tomorrow Kimi release a model better at something, you'd switch to it.
I postulate in practice this won't matter since the space of use cases is so large if Kimi released the absolutely best model at everything they wouldn't be able to serve it (c.f. Mythos).
hn is not a monolith. People here routinely disagree with each other, and that's what makes it great