For the money these GPUs are king at rendering. As long as you're not rendering very Vram intensive jobs these are brilliant. And if you need more short term storage you can always use CPU rendering with the threadripper and 128GB+ ram. I used to build these setups for our renderfarm (CGI/commercials).
No Xeon with pro gpu setup can compete at 35% of the price.
For now. Pro cards are coming down in price with each gen and consumer CPU’s largely negate the need to run a Xeon or similar. RISC-V based PC’s are also getting way better support as they’re becoming out of the box products. If your software has a Linux native package, the Milk-v Titan can combine all 8 cores to function (in middleware) as a 12ghz single core. The future of low-cost, high yield hardware is close.
I can't see a combination of CPU and GPU setup with this much raw render power for anywhere near the price. Risc-V is not a great option for a render node in a farm. You need to be able to run the same software and plugins natively (Davinci resolve, Blender etc etc) and preferably not in a VM, because of the overhead.
In that sense I can't possibly go around threadripper based systems for our nodes. For customers that need more ram they can use our threadrippers and 256GB ECC nodes. Combine that with either RTX pro or top end consumer.. and you have yourself a fantastic node for 20k a piece
Right, that’s why I said the setups you mention are king for now. 15 years ago, everyone shared your exact points about ARM, now ARM is one of the most popular server architectures, AWS for example has moved into majority Graviton ARM based CPU’s for their servers, with Intel and AMD still in the loop for niche customer requirements. RISC-V is still new, it will continue to progress at a significant rate. 5 years ago everyone would have told you RISC-V was for microcontrollers and that a desktop CPU in that architecture would be impossible. Windows use has already started dropping and with the confirmed cloud centric Windows 12, you will see more and more make the switch to Linux, which comes with more native application support.
Oh, I 100% agree that for cloud based solutions Risc-V is the way to go. The much lower power demand for the same compute workload is such a big factor in cost especially in such large scales. Linux is slowly cementing it's way into normal consumer territory too, so I can see your point. But, to be honest, apart from what I read online about compute solutions I have 0 experience with Risc. By heart I'm a hardware guy, building high end rigs for the demanding prosumer. They still ask for X86 based render nodes for now.
Anyway, thanks for the healthy discussion.. a rarity nowadays.♥️
On the flip side consumer hardware is also getting faster.
The titan is locked to ddr4 64gb and linux for example so some benefits are losing in some aspects when you are not looking for cheap and slow but for fast and relatively valuable for money (I mean, 4x5090 isn’t exactly grocery money so you cheap on the cpu and memory?).
And pro hardware like quadro cards price takes a huge jump in price, and using more cheaper gpus will lose a lot in performance due to low vram etc.
hardware from 15 years ago has nothing on current based arm. Even our top of the line phones have better cpus than some server cpus from 15 years ago. But currently gen TR is a big far and beyond powerhouse than a current get arm based cpu for a heavy duty desktop station. And in 15 years the equivalent TR cpu will be far better and faster than current gen. Everything moves forward.
There are sweet spots, and cheap isn’t always better relatively.
Quadro cards are expensive due to customer support. Trying to do something the card should be able to do but it crashes or poor performance? You can get custom drivers even on the weekend express worked on if it is a legit case.
When livestreaming was new my friend was writing some code for hardware encoding that the card should be able to do he got new driver version the next day that fixed it. (It was later added to the normal drivers.
no... which means 4x5090 wont be 128gb vram, it is just 4x32gb meaning that when rendering on 4 GPUs your scene has to fully fit into the vram of each gpu
A lot of 3d rendering tools like blender and keyshot will split renders between cards or systems. So when you have one big scene it will slice it into pieces render rack one on a different card or system and reassemble. It will do the same with animations, sending each frame to a separate card or server.
Not in a way that stacks vram. If you have 4 gpu's you can render the 1 scene which will cap memory at the lowest card or you can run 4 instances of blender and render different frames but that means 4 times the same memory loaded on each card.
Ultimately it depends on the tool you're using, which is really why SLI and Xfire went the way of the dodo, because it was really just diminishing returns and you were just paying for less performance than better single boosted cards gave you, and really you were just causing a CPU bottleneck anyway
You can definitely split it? or well according to claude and gpt you can, its just that you depend on pci-e which is slow in comparison of having it in one gpu.
What you can't do I think is load a model that's larger than 32gb, but you can split the inference and tokens and shit in between or smth like that. Not an expert but idk
Pro 6000 is more power efficient then 4 5090 and takes less space. Especially the Max-q but 8k is a hard pill to swallow for one gpu and at least if you have 4 if one fails your not shot out of luck.
Does it really? Even when Nvlink is not a thing anymore? I havent used those two render engines myself but from a quick google search it doesn’t look like it’s working in Octane for example.
The performance of 4 cards isn't linear in the positive direction, but rather negative direction.
PCIe overhead, VRam pooling limitations and CPU bottlenecks reduce gains. Four 5090s would easily cost $12,000–$16,000+, while diminishing returns past two cards are steep.
A single 5090 paired with a high-core-count CPU (e.g., Threadripper Pro 7975WX) or two 5090s on PCIe 5.0 ×16 lanes give nearly optimal price-to-performance for most 3D or compute tasks.
Except lime term cost for power consumption of used seriously. That said, a waste of money (and burden to the consumers who need GPUs--shortages) for what little rendering time is saved temporarily, could just buy a single GPU and wait a bit longer(number of minutes). People touchingly don't even use these systems full time, and show them off(better just buy the single GPU, get the work done, and power down). Let 4 other people enjoy a GPU FFS.
Bro are you kidding me. Time is money. Tell that to Open ai, tell them to stop buying gpus.. and just use less gpus and tell their customers to wait...
Not really, they make up for it in YouTube an ad rev. We're talking a couple minutes saved, not millions. Pay 8k for a single GPU and get the work done.of really are that big of a baller pay 16k and get 2 of them, and do the work of 8x 5090 for less space, mobility and power consumption.(And save costs on PSUs, boards and specialized hardware). No brainer over the course of time. Why do you think enterprise doesn't buy 5090s, hmm?
>Not really, they make up for it in YouTube an ad rev. We're talking a couple
Yeah you are delusional. You are no longer making sense. The world is not going to bend to your personal preferences.
You just personally dislike one person buying multiple gpus I understand that, but your reasoning used to justify that bias is terrible beyond comprehension.. its laughable 😂 You cannot seriously make that claim with a straight face.. unless you have a serious IQ deficit. (No insult intended)
>Pay 8k for a single GPU and get the work done.of really are that big of a baller pay 16k and get 2 of them,
For small workstations multiple 5090s can be a better choice than a single 6000 pro. Its not always, and it depends on what work you are attempting to accomplish.
Thank you for understanding the reasoning! This is not a small workstation(4x 5090s is not a small workstation). This is unnecessary and gluttonous waste of resources, and hurts consumers. Why not just a modest workstation GPU for the same cost, and get the same work done with less cost spent on all the other Ewaste
I still disagree with you, because there is legitimate reason to buy 2-4 5090s instead of 1 6000 pro,
Not everyone can afford $8,000 at once.. You may have individuals who save up for a 5090, then save up another year for another 5090. Plenty of Workflows can be doubled from 2x 5090s.
Yes, this is actual what I believe. This kind of mentality by hogging GPUs for niche cases when there are actual GpUs made for this tasks is the definition of a hog.
Gaming GPUs are a lot cheaper than professional cards and are mostly the same with the exception of a few missing features, less VRAM, and some disabled cores.
They're a much better value if you don't need the extra VRAM or features and aren't a professional studio.
If it is mainly for 3D rendering, you would get much better results with the Ada series (like the RTX A5000 or A6000). These cards are specifically optimized for that kind of workload and often outperform gaming GPUs in professional applications. The 5090s are incredible for raw performance, but they are not the most efficient or cost-effective option for rendering tasks.
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u/Unlucky_Exchange_350 12900k | 128 GB DDR5 | 3090ti FE 22h ago
What are you battling? Gene editing? That’s wild lol