“I’ve been saving for months to get the Corsair Dominator 64GB CL30 kit,” one beleagured PC builder wrote on Reddit. “It was about $280 when I looked,” said u/RaidriarT, “Fast forward today on PCPartPicker, they want $547 for the same kit? A nearly 100% increase in a couple months?”
I just got a 2x64GB 6000 kit before its price skyrocketed by like $130. I saw other kits going up, but had no clue I timed it so well.
…Also, why does “AI” need so much CPU RAM?
In actual server deployments, pretty much all inference work is done in VRAM (read: HBM/GDDR); they could get by with almost no system RAM. And honestly most businesses are too dumb to train anything that extensively. ASICs that would use, say, LPDDR are super rare, and stuff like Hybrid/IGP inference is the realm of a few random folks with homelabs… Like me.
I think ‘AI’ might be an overly broad term for general server buildout.
Same memory production capacity can be allocated to ddr5 or to hbm and openai signed contracts with sk hynix and samsung, the two largest ram manufacturers in the world, and bought a significant percentage of next year’s production.
DDR5 prices started spiking as that deals impact propagated through the supply chain. I bought a 2x32 6800 Cl30 kit for 195 euro 12 days ago. It was 330 euro 4 days later.
…Is it that interchangeable?
TBH I know little of memory fabs and HBM ICs, but I know (say) TSMC can’t just switch from a power-optimized process to a high frequency one at the drop of a hat.
Slightly different part, same process. The bigger bottleneck is packaging - HBM is 3d stacked.
Ah. Yeah. And its on the fab to do that.
I always though it’d be cool for CPUs to switch to packaged RAM, too. Samsung apparently tried to do it with Wide I/O for mobile ARM stuff, but it never caught on.
There was a recentish model, qwen next that was advertised as smth that can be run entirely on RAM.
They can ALL be run on RAM, theoretically. I bought 128GB so I can run GLM 4.5 with the experts offloaded to CPU, with a custom trellis/K quant mix; but this is a ‘personal use’ tinkerer setup basically no one but hobbyists will touch.
Qwen Next is good at that because its very low active parameter.
…But they aren’t actually deployed that way. They’re basically always deployed on cloud GPU boxes that serve dozens/hundreds of people at once, in parallel.
AFAIK the only major model actually developed for CPU inference is one of the esoteric Gemma releases, aimed at mobile. And the bitnet experiments, which aren’t very big so far.
(In case it’s not obvious, this is my special interest, and I’m happy to ramble on about how to set up ‘niche gaming rig hybrid models’ for anyone interested).
I for one would enjoy triggering your unskippable cutscenes in setting up local CPU based AI if it can work on Linux with an older amd card.
Don’t have funds for anything fancy, but would be interesting in playing around with it. Been wanting to get something like that setup for home assistant.
You can use Vulkan fairly easily as long as you have 8G vram
https://blog.linux-ng.de/2025/09/27/running-llms-with-llama-cpp-using-vulkan/
Plenty of folks do AMD. A popular homelabsetup is 32GB AMD MI50 GPUs, which are quite cheap on eBay. Even Intel is fine these days!
But what’s your setup, precisely? CPU, RAM, and GPU.
I have a MI50/7900xtx gaming/ai setup at homr which in i use for learning and to test out different models. Happy to answer questions