“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?”
People buying RAM: oh no, what do we do?
People buying GPUs: first time?
What?
You think this is the first ram crunch?
It’s not even the first one in this decade…
Well, I was aware RAM prices fluctuate.
I’ve never been so unfortunate when buying larger RAM, or building a new system with a new DDR version.
They don’t real fluctuate, it’s more oscillating.
Sometimes it’s “normal” but due to a wide range of issues that can change quickly and stay that way for months because everyone waits till prices go down. So as they go down, people stop waiting,
Those are the same people.
Nice article but the numbers are a lot lower here in the EU.
While there is some pricing increase it’s currently more around 50% and not 100%.
The selected kit is also extremely expensive (350€ was ~300€) - similar kits are available for a lot less (270€ was ~180€) - so I doubt that anyone was buying it in the first place.
I also think it’s not completely AI related but more likely that this is another RAM price fixing scandal happening right now. Pretty much the same that we see today happend in 2017-2018.
Europe is also hit hard. The kit I was about to buy increased from 850 to 2K euro…
Bruh, my whole mid-to-high range gaming PC costs 850 to 2K euro. What is the intended use of such an expensive RAM kit? Is it LLMs again?
Scientific applications. My lab has a PC running 196GB RAM for processing 3D and 4D microscopy voxel datasets.
Sounds more like the applications require some serious optimizations to me…
Not LLM in this case actually. Virtualization mostly with qubes OS
Doesn’t Windows 11 in practice require even more memory than Windows 10 to operate with decent performance?
Meanwhile my Linux gaming PC seems to actually use less memory than back when it was a Windows machine.
My work laptop was upgraded to Windows 11 and performance has severely suffered.
As someone who usually uses 3 monitors (sometimes 4) and does GIS, it’s an issue.
Oh yeah. If you’ve got 4 GB ram, win 11 is going to absolutely skullfuck that machine.
Constant surveillance will do that. Legit “telemetry” wouldn’t be using that much processing power.
I’m thinking Recall is just Microsoft trying to cut costs on their servers processing all the surveillance, and force users to pay the costs of all the extra electricity and equipment needed.
Nah it’s probably just Edge (aka Chrome) all over the new UI.
That wouldn’t show in the task manager as telemetry.
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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.
If I’m following what you mean by packaged RAM, Apple does that. It’s fast, but you can’t upgrade it.
That’s (as I understand it) a misconception.
Apple attaches their laptop RAM the same way all smartphones do. It’s a wide bus with LPDDR, which makes it an unusual configuration amongst laptops, but it’s technically conventional. And relatively cheap.
AMD’s Strix Halo chips are the same. Apple could use LPCAMM to make the memory upgradable if they wanted, they just… don’t.
When we talk ‘packaging’, we’re talking putting chips on advanced substrates with denser wires than one could possibly get on a motherboard (or a ‘mini’ motherboard which is kinda what Apple/smartphone RAM is packaged on), stuff silicon fabs have to do:
https://www.tsmc.com/english/dedicatedFoundry/services/advanced-packaging
And HBM falls into this bucket. The way its hooked up to the processor is physically different than PC RAM sticks, or Apple’s RAM. This is mostly not done on consumer stuff because its very expensive, and most of TSMC’s advanced packaging production capacity is reserved for server stuff.
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.
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
Looks like I’m running an AMD Ryzen 5 2600 CPU, AMD Radeon RX 570 GPU, and 32GB RAM
4GB VRAM
Mmmmm… I would wait a few days, and try a GGUF quantization of Kimi Linear once its better supported: https://huggingface.co/moonshotai/Kimi-Linear-48B-A3B-Instruct
Otherwise you can mess with Qwen 3 VL now, in the native llama.cpp UI. But be aware that Qwen is pretty sycophantic like ChatGPT: https://huggingface.co/unsloth/Qwen3-VL-30B-A3B-Instruct-GGUF/blob/main/Qwen3-VL-30B-A3B-Instruct-UD-Q4_K_XL.gguf
If you’re interested, I can work out an optimal launch command. But to be blunt, with that setup, you’re kinda better off using free LLM APIs with a local chat UI.
Thanks for the info. I would like to run locally if possible, but I’m not opposed to using API and just limiting what I surface.
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/
The key is which model, and how.
For the really sparse MoEs, you might be better off trying ik_llama.cpp, especially if you are targeting a ‘small’ quant. But the dense Gemma models (as good as they are) are probably not the best choice for 8G RAM these days.
Only got 4G vram, unfortunately
I suspect RAM may become increasingly useful with the shift from pure chat LLM to connected agents, MCP, and catching results and data for scaling things like public Internet search and services.
When I think of database system server software, a lot of performance gains are from keeping used data in RAM. With the expanding of LLM systems and it’s concerns, backing data, connective ness, and need for optimisation, a shift to caching and keeping in RAM seems to suggest itself. It’s already wasteful/big and operates on a lot of data, so it seems plausible that would not be a small cache.
Yeah, exactly… In other words, ‘general server buildout.’
why does “AI” need so much CPU RAM
It doesn’t really, though CPU inference is possible/slow at 256+gb. The problem is that they are making HBM (AI) ram instead of ddr4/5.
First crypto miners came for my video cards, then AI came for my DIMMS…
Next tech-sector grift will probably go for our network adapters or some shit…
I’ve got a stack of old 14.4 modems I’ll sell them if they’ll grift on that for a bit.
next the tech-bros will come for you and there will be nobody left to speak up.
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The market can remain irrational for far longer than you can remain solvent
The thing is, the “people” propping it up, are massive tech companies with collectively trillions of dollars to burn on this thing that is making their stock prices soar.
They have no incentive as the primary investors doing the circular buying to stop. The big problem here is the stock market provides awful incentives to everyone.
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This bubble is largely self dependent with all invested parties incentivised to prop it up. Completely different type of situation.
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No. The housing crash really started to go off when regular people could not pay their bills. These arent regular folks here. These are mega corporations.
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Are you like… just not reading the parts where I explain how these are massively different situations?
2 things can be bubbles while being massively different in the forces at play.
Just in time for all those windows PCs that MS is trying to force people to upgrade
Waiting for upcoming patch tuesday to see if mas scripts work
Wow I just checked the laptop kit I bought a month ago it is 50% more E: it’s fucking over 100% more now wow it was a 64gb sodimm kit I got for 280AUD and now it is 700AUD fucking hell
soon the bubble will burst and RAM will be so cheap! (I hope)
I don’t think the bubble bursting will slow AI that much, it’ll just be a round of hot potatoe over, the losers will lose their money and others will come in hoping to be profitable since they can skip a bunch of R&D costs.
AI is overhyped, but just like the internet after the dotcom bubble burst, it’s not going anywhere.
Plus I suspect that this time will be a dollar collapse rather than stock market collapse, which would mean prices would go up even more.
It always does. I remember buying my DDR4 RAM 200€, and two months later the same kit was 550€. Some month later it was back at 220€.
RAM used to cost 8x that. It’s the reason why HP cases have locks.
Buy one RAM and you get two GPUs thrown in for free!
Old computer blew up, had to buy a new one. Nice 128gb ddr5. Just mobo, mem, cpu. Cpu is a rhyzen 9 9700
The memory was well over 40% of the cost, wtf?
Uhm what exactly do you need 128GB for? xD
Probably VMs.
not OP, but I guess that’s futureproofing, 128GB RAM should be more than enough for a long time
If they have their computers blow up they may not reach that far future point.
It really depends on your workflows/use, whether you make use of a lot of RAM, and possibly even 128 GB today. That kind of size is certainly niche.
Laughs in ddr4…
It also got affected.
God fucking damnit, can’t I even be poor in peace, JFC!
Is DDR3 affected too?
Although it’s ambiguous how much of this is due to AI data centres and how much is the natural ramp-down of DDR4 production.
DDR3 also increased substantially in price a few years after DDR4 became available.
Im still gaming on a 15 year old cpu and ddr3, lol. Playing a decent amount of new games. Only one that wont run is alan wake 2 and that may be because of linux .
Amd fx 8 core.
Indeed awful. AFAIU, it is stockpiling HBM memory ahead of next generation “GPUs”, rather than existing product volume. I’m especially disgusted that prices in non-tariff countries are higher than in US. If this were to last, gddr5/6 computer ram would start to make sense. NVIDIA has been behind starving memory supplies for competing platforms (usually AMD) in the past.
This pricing is both huge inflation, but also huge drop in sales, because we have to wait for it to get sensible.
The non tariff nations getting hit with higher then us prices just shows how little they think of customers. They assume we will pay, they feel entitled to our money. The products have stagnanted, the prices are made up and clearly based on nothing but good old fashion “fuck you pay me” logic. My guess is they are assuming “AI” companies will just buy whatever they make.
If people keep buying however they will keep doing this. If the market drops out from them (AI bubble bursting at the same time people cut back on buying new systems) then they will likely ask for bailouts (your money again).
Apple specifically is provably charging countries without tariffs: https://iphone-worldwide.com/
Have the world subsidize US sales, just because they’re used to paying a little more. Not surprised that other goods would use same strategy.
Its just naked greed, the sooner the world can move away from america and these companies the better.
Welp, it’s probably about time for my PC to break its RAM again.
Back to virtual RAM on disk. At least we have SSDs now.
Genuine question here, for a “normal” computer user, say somebody who :
- browses the Web
- listens to music, play videos, etc
- sometimes plays video games, even 2025 AAAs and already has a GPU relatively recent and midrange, say something from e.g. 2020
- even codes something of a normal size, let’s say up to Firefox size (which is huge)
… which task does require more than say 32Go?
You probably dont but 32gb ddr5 is minimum 200$ right now for the slowest.
For normal use like that 16GB is generally just fine. Some games can use enough that you’ll need to close Firefox and other RAM hungry programs though.
As far as needing more than that, people who do heavy design work or edit videos and that kind of thing generally do. For example 32GB running Fusion in Davinci Resolve can be a bit limiting sometimes with higher resolution or 10 bit footage.
If by normal you average, they don’t even really need 16gb.
Creative work can gobble up ram, heavy ass multitasking does as well.
So it’s more in the digitally productive professional or hobbyist cases where you need such amounts as a person.For development high amounts of rams can be useful for all sorts of stuff, it’s not just compiling, but also testing, though 32 is often enough.
For a normal user, 16G is still enough.
But for a power user like me, a Dev, with multiple IDE open, multiple browsers, a database manager with a dockerized DB, I’m basically at 96-98% RAM all the time.
But even then, if you use a local AI, prepare to loose multiple Gigs to it.
I already used more than 30 Gigs on one LLM (dolphin-mixtral:8x7B for the curious), when I tried testing it, and a more reasonable Mistral:7B still took me like 4Gigs just to run.I don’t know but I am constantly hitting the RAM limit with 16Gb of RAM with around 20-30 open tabs and other apps, both on Linux and Windows
I bought 16gb of ddr4 for 110eu back in 2018. Welcome back to the DDR wars, with NAND soon to follow.
