Not an AI guy, but I do like using niche hardware wrong to get results cheap. Can anyone tell me what this would be like for gaming or general computing? My 1660 super was a budget pick when I got it back in '18.
A lot of data center GPUs don't have display outputs or cooling. So you would need to figure out how to cool them.
Cooling wouldn't be too hard, I'm currently overengineering an Xbox 360 for that so I've done a good deal of learning. Getting of to display video is outside my skillset though.
A cursory search says somewhere between a 3060 and 4060, which seems about right. Games that parallelize well across the GPU cores will benefit, though that benefit will be niche if it exists at all. HBM2 memory is weird for gaming.
You'd see some benefit for sure, but this really is better suited to parallel computing, given the emphasis on CUDA core counts and memory bandwidth. You may also find you run into some latency, since it requires selecting the V100 as your primary GPU but a secondary card as the video output. Integrated GPUs work well for this, since your motherboard may already have this ability. Otherwise, you could use it in tandem with a 1030 or similar to get display out.
So I'm picking up that it's not a viable alternative for the desperate?
Probably not your best option, no
Yeah but the 0 point doing this unless you want to run AI models for some reason. These GPUs can't do video game graphics so this isn't a solution to the GPU shortage.
This is a bit like me writing an article about NASCAR, now I can turn left whenever I want. But I haven't magically acquired a functional vehicle for a fraction of its value. I've purchased a second hand specialist product that is usually useless outside of that environment.
The article talks a lot trash about AMD and ROCm but vulkan works fine too. In fact from a datacenter GPU standpoint there is an AMD option called the V620 available on US EBay that I was able to haggle to $350, with 32GB VRAM, 512GB/s bandwidth, and runs the same Qwen-3.6-27b at about 20t/s. I would argue that's even more cost effective.
It requires a few of the same fan shenanigans this guy did but there is no need to pull specific past software versions to make it usable in Linux
Here I was expecting a graphics demo to blow our collective minds but instead I got a story about a local LLM for cheap. It is . I should have known better.
Were I the author / tech cobbler here, I'd be concerned that too much time with an LLM, local or otherwise, might erode or dull my apparently fairly sharp reasoning and tech skills. (Clarification: Not my sharpness, theirs. I'm a potato.)
Other thoughts: For a minute I thought this whole thing was a tribute to, or a troll in the manner of, that one Redditor that always spun their stories around to being about their dad beating them with jumper cables.
Also, my old PC developed an issue like the warm reboot problem, except with the network interface. I couldn't just restart, I had to power off and back on. I never did bother to find out whether it was early signs of hardware failure or whether it was an old hardware / newer kernel mismatch.
They cannot run graphics
The change of the meaning of the G in GPU from "graphics" to "general" is even less well documented and used than the "V" of DVD changing from "video" to "versatile".
Indeed it only occurred to me what it must have changed to and to go looking to confirm after seeing your comment.
And frankly they ought to have changed the name to something like "MPPU" if they wanted it to stick (massively parallel).
Why tho?
Fair enough
You're in the wrong community if you're asking questions like that.
Ever watched bringus studios? Man played games on a drive through computer. As the old saying goes all hardware is good hardware if you know what to do.
Seems like an awful lot of trouble to save $100 not buying a 5060 Ti that also has 16GB.
448 GB/s memory vs 900 GB/s and at a cheaper price.
Sure it's got a lot of VRAM, but the 4080 has five times the compute power.
You're not getting a 4080 for $200 though...
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