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.
this post was submitted on 19 Jul 2026
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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.
A lot of data center GPUs don't have display outputs or cooling. So you would need to figure out how to cool them.
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.
Why tho?
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.
I cant get past the new hair cut. He looks like a bond villains lacky now lol
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.
RogerSimon10! (The jumper cables guy)
Unless maybe he was the similar but later hell-in-a-cell guy? I don’t remember anymore.
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).
Back in my day, we memorized logarithm tables and we liked it!
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 $350, with 32GB VRAM, 512GB/s bandwidth, and runs the same Qwen-3.6-27b at about 20t/s. I would argue that's even more cost effective.
It requires a few of the same fan shenanigans this guy did but there is no need to pull specific past software versions to make it usable in Linux
Honestly even for the prices of around 500$ that I'm seeing it for it looks like a pretty good value to get 32gb of vram. I see it says 300w on AMD's product page for it does it have any way of power limiting the card to get more efficiency/less heat?
I spent a lot of time researching and testing different methods for that, the only thing that worked was LACT in Linux. Using that I was able to undervolt 100mV and GPU power usage dropped about 10%. On my B450 ITX board with a Ryzen 2400GE CPU the entire system pulls 30w idle from the wall, and about 300w inferencing with VRAM filled. (330w before LACT).
My fan solution ended up being to buy the 80mm 3d-printed shroud off ebay, the fan that came with it was super loud so I switched to an arctic p8 Max, and control it with the motherboard targeting a t-sensor header with the probe attached to the backplate.
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Sure it's got a lot of VRAM, but the 4080 has five times the compute power.
That's fine I just need to display pictures of your mom (they are very large) (/s)
eBay has some rad Chinese mezzanine boards for these guys too. Nvlink works and everything lol
Cool mezzanine boards, but can we talk about your dope af custom jig for offset mounting arbitrary boards?
I appreciate the kind words! Until recently, my day job was CAD monkey. I wanted to consolidate the hardware I was cobbling together, found a cheap 8 GPU mining rig and some extra 2020 extrusions to play with.
The seller for the mezzanine said it followed the mATX mounting hole pattern, (it does but is ~75% in the width and doesn't use all the points). I have a tendency to overthink designs and kind of stalled for a bit before finally taking the plunge and whipping up these struts. I used some brass heat set inserts to accept the standoffs and everything pretty much went right together lol
Damn, even cooler than I expected 🎸 Thank you for the extra details and picture!
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Seems like an awful lot of trouble to save $100 not buying a 5060 Ti that also has 16GB.
The 5060 Ti does not support Nvlink though.
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