cirrusfan

This model is exactly what you’d want for your resources. GPU for prompt processing, ram for model weights and context length, and it being MoE makes it fairly zippy. Q4 is decent; Q5-6 is even better, assuming you can spare the resources. Going past q6 goes into heavily diminishing resources.

Anthropic might have the best product for coding but good god the experience is awful. Random limits where you _know_ you shouldn’t hit them yet, the jankiness of their client, the service being down semi-frequently. Feels like the whole infra is built on a house of cards and badly struggles 70% of the time.

I think my $20 openai sub gets me more tokens than claude’s $100. I can’t wait until google or openai overtake them.

I think it depends on what you use it for. Coding, where time is money? You probably want the Good Shit, but also want decent open weights models to keep prices sane rather than sama’s 20k/month nonsense. Something like a basic sentiment analysis? You can get good results out of a 30b MoE that runs at good pace on a midrange laptop. Researching things online with many sources and decent results I’d expect to be doable locally by the end of 2026 if you have 128GB ram, although it’ll take a while to resolve.

If it sounds too good to be true…

I find it really surprising that you’re fine with low end models for coding - I went through a lot of open-weights models, local and "local", and I consistently found the results underwhelming. The glm-4.7 was the smallest model I found to be somewhat reliable, but that’s a sizable 350b and stretches the definition of local-as-in-at-home.

Huh? What prevents you from installing them "all at once"? The downside is obviously a long stretch of no sun, and for Europe winter being both low solar production and high energy demand due to heating which the soon-to-be-cheap grid scale batteries don’t really fix. The logistics of PV don’t seem difficult though - it seems by far the easiest of the power generation methods, even if the synchronization can get a bit tricky in a large grid.

I get a slow-but-usable ~10tk/s on kimi 2.5 2b-ish quant on a high end gaming slash low end workstation desktop (rtx 4090, 256 gb ram, ryzen 7950). Right now the price of RAM is silly but when I built it it was similar in price to a high end macbook - which is to say it isn’t cheap but it’s available to just about everybody in western countries. The quality is of course worse than what the bleeding edge labs offer, especially since heavy quants are particularly bad for coding, but it is good enough for many tasks: an intelligent duck that helps with planning, generating bog standard boilerplate, google-less interactive search/stackoverflow ("I ran flamegraph and X is an issue, what are my options here?” etc).

My point is, I can get somewhat-useful ai model running at slow-but-usable speed on a random desktop I had lying around since 2024. Barring nuclear war there’s just no way that AI won’t be at least _somewhat_ beneficial to the average dev. All the AI companies could vanish tomorrow and you’d still have a bunch of inference-as-a-service shops appearing in places where electricity is borderline free, like Straya when the sun is out.

> but I have to baby sit the process and think whether I want to skip or retry a failed copy

Do you import originals or do you have the "most compatible" setting turned on?

I always assumed apple simply hated people that use windows/linux desktops so the occasional broken file was caused by the driver being sort-of working and if people complain, well, they can fuck off and pay for icloud or a mac. After upgrading to 15 pro which has 10 gbps usb-c it still took forever to import photos and the occasional broken photos kept happening, and after some research it turns out that the speed was limited by the phone converting the .heic originals into .jpg when transferring to a desktop. Not only does it limit the speed, it also degrades the quality of the photos and deletes a bunch of metadata.

After changing the setting to export original files the transfer is much faster and I haven’t had a single broken file / video. The files are also higher quality and lower filesize, although .heic is fairly computationally-demanding.

Idk about Android but I suspect it might have a similar behavior