I wonder why everyone keep saying "just put more VRAM" yet no cards seem to do that. If it is that easy to compete with Nvidia, why don't we already have those cards?
Maybe because only AI enthusiasts want that much VRAM, and most of them will pony up for a higher-end GPU anyways? Everyone is suggesting it here because that's what they want, but I don't know if this crowd is really representative of broader market sentiment.
There are a lot of local AI hobbyists, just visit /r/LocalLLama to see how many are using 8GB cards, or all the people asking for higher RAM version of cards.
This makes it mysterious since clearly CUDA is an advantage, but higher VRAM lower cost cards with decent open library support would be compelling.
because the cards already sell at very very good prices with 16GB and optimizations in generative AI is bringing down memory requirements. Optimizing profits means yyou sell with the least amount of VRAM possible not only to save the direct cost of the RAM but also to guard future profit and your other market segments. the cost of the ram itself is almost nothing compared to that. any intel competitor can more easily release products with more than 16GB and smoke them. Intel tries for a market segment that was only served by gaming cards twice as expensive up until now. this frees those up to be finally sold at MSRP.
> If it is that easy to compete with Nvidia, why don't we already have those cards?
Businesswise? Because Intel management are morons. And because AMD, like Nvidia, don't want to cannibalize their high end.
Technically? "Double the RAM" is the most straightforward (that doesn't make it easy, necessarily ...) way to differentiate as it means that training sets you couldn't run yesterday because it wouldn't fit on the card can now be run today. It also takes a direct shot at how Nvidia is doing market segmentation with RAM sizes.
Note that "double the RAM" is necessary but not sufficient.
You need to get people to port all the software to your cards to make them useful. To do that, you need to have something compelling about the card. These Intel cards have nothing compelling about them.
Intel could also make these cards compelling by cutting the price in half or dropping two dozen of these cards on every single AI department in the US for free. Suddenly, every single grad student in AI will know everything about your cards.
The problem is that Intel institutionally sees zero value in software and is incapable of making the moves they need to compete in this market. Since software isn't worth anything to Intel, there is no way to justify any business action isn't just "sell (kinda shitty) chip".
I believe that VRAM has massively shot up in price, so this is where a large part of the costs are. Besides I wouldn't be very surprised if Nvidia has such strong market share they can effectively tell suppliers to not let others sell high capacity cards. Especially because VRAM suppliers might worry about ramping up production too much and then being left with an oversupply situation.
This could well be the reason why the rumored RDNA5 will use LPDDR5X/LPDDR5X instead of GDDR7 memory, at least for the low/mid range configurations (the top-spec and enthusiast configurations AT0 and AT2 configurations will still use GDDR7 it seems).
There does seem to be a grey market for it in China. You can buy cards where they swap the memory modules with higher capacity ones on Aliexpress and ebay.
Ryzen AI max+ 395 128GB can do 256GBps so lets put all these "ifs" to bed once for all. That is absolutely no brainer to drop more RAM as long as there is enough bits in address space of physical hardware. And there usually is, as same silicons are branded and packaged differently for commercial market and for consumer market. Check up how chinese are doubling 4090s RAM from 24 to 48GB.
fwipsy|5 months ago
vid|5 months ago
This makes it mysterious since clearly CUDA is an advantage, but higher VRAM lower cost cards with decent open library support would be compelling.
unknown|5 months ago
[deleted]
blkhawk|5 months ago
betimsl|5 months ago
bsder|5 months ago
Businesswise? Because Intel management are morons. And because AMD, like Nvidia, don't want to cannibalize their high end.
Technically? "Double the RAM" is the most straightforward (that doesn't make it easy, necessarily ...) way to differentiate as it means that training sets you couldn't run yesterday because it wouldn't fit on the card can now be run today. It also takes a direct shot at how Nvidia is doing market segmentation with RAM sizes.
Note that "double the RAM" is necessary but not sufficient.
You need to get people to port all the software to your cards to make them useful. To do that, you need to have something compelling about the card. These Intel cards have nothing compelling about them.
Intel could also make these cards compelling by cutting the price in half or dropping two dozen of these cards on every single AI department in the US for free. Suddenly, every single grad student in AI will know everything about your cards.
The problem is that Intel institutionally sees zero value in software and is incapable of making the moves they need to compete in this market. Since software isn't worth anything to Intel, there is no way to justify any business action isn't just "sell (kinda shitty) chip".
rocqua|5 months ago
kokada|5 months ago
GTP|5 months ago
Given the high demand of graphic cards, is this a plausible scenario?
robotnikman|5 months ago
danielEM|5 months ago
PunchyHamster|5 months ago
qudat|5 months ago
agilob|5 months ago
izacus|5 months ago
- less people care about VRAM than HN commenters give impression of
- VRAM is expensive and wouldn't make such cards profitable at the HN desired price points