Hacker News moment

$10k is well outside my budget for frivolous computer purchases.

It would be plenty in-budget if the software part of local AI was a bit more full-featured than it is at present. I want stuff like SSD offload for cold expert weights and/or for saved/cached KV-context, dynamic context sizing, NPU use for prefill, distributed inference over the network, etc. etc. to all be things that just work for most users, without them having to set anything up in an overly error-prone way. The system should not just explode when someone tries to run something slightly larger; it should undergo graceful degradation and let them figure out where the reasonable limits are.

But it's well within the budget of a small company that wants to run a model locally. There are plenty of reasons to run one locally even if it's not state of the art, such as for privacy, being able to do unlimited local experiments, or refining it to solve niche problems.

yeah, but if you really really wanted to and/or your livelyhood depended on it, you probably could afford it.

99.97% of HN users are nodding… :)

There are way too many good uses of these models for local that I fully expect a standard workstation 10 years from now to start at 128GB of RAM and have at least a workstation inference device.

or if you believe a lot of HN crowd we are in AI bubble and in 10 years inference will be dirt cheap when all of this crashes and we have all this hardware in data centers and it won't make any sense to run monster workstations at home (I work 128GB M4 but not run inference, just too many electron apps running at the same time...) :)

> I work 128GB M4 but not run inference, just too many electron apps running at the same time.

This is somewhat depressing - needing a couple of thousand bucks worth of ram just to run your chat app and code/text editor and API doco tool and forum app and notetaking app all at the same time...

Inference will be dirt cheap for things like coding but you'll want much more compute for architectural planning, personal assistants with persistent real time "thinking / memory", as well as real time multimedia. I could put 10 M4s to work right now and it won't be enough for what I've been cooking.

That's kind of a specific percentage. What numbers did you use to get there?

Just have to reclassify it as non-frivolous then. $10k's not a lot for something as important as a car, if you live somewhere where one is required. Housing is typically gonna cost you more than $10k to own. I probably spend close to $10k for food for 1.5 years.

So if you just huff enough of the AI Kool aid, you too can own a Mac Studio. Or an M5 MacBook. Or a dual 3090 rig.

I'm running it on my Intel Xeon W5 with 256GB of DDR5 and Nvidia 72GB VRAM. Paid $7-8k for this system. Probably cost twice as much now.

Using UD-IQ4_NL quants.

Getting 13 t/s. Using it with thinking disabled.

I get 20 t/s on the UD-Q6_K_XL quant, Radeon 6800 XT.

For some reason you were being downvoted but I enjoy hearing how people are running open weights models at home (NOT in the cloud), and what kind of hardware they need, even if it's out of my price range.

you have proved my point

In where I am living, 10k USD is a little more than 3 years worth of rent, for a relatively new and convenient 2 bedroom apartment.

Yes, I am in SEA. Home internet here costs 10$ per month.

My point was: not every person browsing this site has high living standard, and the ability to spend 10k on computing is a privilege.