I don't want to argue here, but once models are trained, using them is quite cheap. Also in the last few months most improvements I've seen are in the smaller sized models, which might make using models even cheaper.
No.
>Do you make a frontier model orchestrate it?
Also no.
>Are you running with llama.cpp?
Yes, on Arch Linux.
>Sorry for the barrage of questions
No worries.
My Qwen testing has been with Hermes trying to do mundane (to me) things that hosted models understandably refuse to do, even open-weight ones like Deepseek V4.1 Flash. Example: I tried to get it to find a torrent for $tvshow and add it to qbittorrent (connected to hermes via MCP already). It certainly tried and I think frontier models would have done better. My biggest issue was context space more than anything else. I had to drop down a quant level to increase it to 128k. On 64k it was constantly compacting.
Likewise if models become commoditized, it's raising the value of the existing hardware (you'd expect the hardware owner to keep a bigger slice of the surplus when that's the scarce component).
For model improvements to be bad for the value of hardware, what you'd need is for demand for intelligence to be inelastic. But everything we've seen so far suggests that is not the case: the demand for intelligence (whether human or artificial) is highly elastic both in price and in quality.
until the other guys comes out with a slightly better model, then using yours wont be cheap enough.