I’m obviously not the intended audience for this, and I understand this hardware is not useful for it, but I can’t help but feel an extra twinge of disappointment that there’s no mention of PC gaming anywhere in a post about GPUs in the comments here on HN. It says a lot.
Benchmarking 15 “E-Waste” GPUs with Modern Workloads
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Re: Benchmarking 15 “E-Waste” GPUs with Modern Workloads
#52Re: Benchmarking 15 “E-Waste” GPUs with Modern Workloads
#53Have you tried 27B class models like qwen3.6?
Re: Benchmarking 15 “E-Waste” GPUs with Modern Workloads
#54I’m obviously not the intended audience for this, and I understand this hardware is not useful for it, but I can’t help but feel an extra twinge of disappointment that there’s no mention of PC gaming anywhere in a post about GPUs in the comments here on HN. It says a lot.
Maybe you'd be interesting in r/gaming or something similar. Around these parts, it's all about taking something and using for something it was never intended to be used. Using a GPU to run a game sounds exactly the opposite and a very lame use of that GPU.
Is this satire? I literally was hoping the article would be about how decommissioned _data center_ GPUs were repurposed for home PC gaming, the exact thing hacker news is ostensibly supposed to be about? It opens making a point about how the only cheap GPUs with lots of ram are e.g. K80s, which are hardly meant for gaming.
Re: Benchmarking 15 “E-Waste” GPUs with Modern Workloads
#55No mention of the venerable Tesla P4. 75W peak, 8GB VRAM, about $80 (£60). I have 6x P4s, a Xeon E5 2696v3 (36 threads, 3.8ghz peak but all core turbo unlocked, so 6 cores at 3.8Ghz - about 8 cores at 3.5ghz, or all cores at 3.1ghz), 48GB DDR4, all fit into a micro atx case running on a 650W MSI psu. This gives me a virtual 48GB GPU (llama.cpp ftw) to backup that 48GB of RAM. I typically see scores of at least 7-12t/…
> about $80 (£60) Man, I wish I lived where you guys lived.
Re: Benchmarking 15 “E-Waste” GPUs with Modern Workloads
#56Earlier quoted context omitted.
Maybe you'd be interesting in r/gaming or something similar. Around these parts, it's all about taking something and using for something it was never intended to be used. Using a GPU to run a game sounds exactly the opposite and a very lame use of that GPU.
> Around these parts, it's all about taking something and using for something it was never intended to be used Is this satire? I literally was hoping the article would be about how decommissioned _data center_ GPUs were repurposed for home PC gaming, the exact thing hacker news is ostensibly supposed to be about? It opens making a point about how the only cheap GPUs with lots of ram are e.g. K80s, which are hardly me…
Re: Benchmarking 15 “E-Waste” GPUs with Modern Workloads
#57Earlier quoted context omitted.
> Around these parts, it's all about taking something and using for something it was never intended to be used Is this satire? I literally was hoping the article would be about how decommissioned _data center_ GPUs were repurposed for home PC gaming, the exact thing hacker news is ostensibly supposed to be about? It opens making a point about how the only cheap GPUs with lots of ram are e.g. K80s, which are hardly me…
Wait a few years, and we're all gaming on decomissioned data center GPUs ;-)
Re: Benchmarking 15 “E-Waste” GPUs with Modern Workloads
#58Earlier quoted context omitted.
That's great. Personally, I'd interested in Qwen3.6-27B and deepseek V4 flash (or pro), with contexts above 60k. They seem to be popular and have good coding performance. I'd appreciate numbers on a single or two GPUs where a quantized version fits reasonably into the VRAM (Qwen in 16 or 24GB). 4 older GPUs approach a used 3090 in price, and the 3090 has better support for speedups like MTP. So cheaper but slower loo…
No problem. Varying context size is a common request I've been getting as well. Personally I'm looking forward to seeing how much we can cram into the ancient K80's 24GB of VRAM :0
I just saw this simple patch to enable MTP (potentially 2x performance) on older GPUs (Kepler etc), so maybe it will work for you
https://github.com/ggml-org/llama.cpp/pull/25680
Also, for Qwen, the 4 bit _XL quantization seems to have a good balance of performance to size.
Re: Benchmarking 15 “E-Waste” GPUs with Modern Workloads
#59No mention of the venerable Tesla P4. 75W peak, 8GB VRAM, about $80 (£60). I have 6x P4s, a Xeon E5 2696v3 (36 threads, 3.8ghz peak but all core turbo unlocked, so 6 cores at 3.8Ghz - about 8 cores at 3.5ghz, or all cores at 3.1ghz), 48GB DDR4, all fit into a micro atx case running on a 650W MSI psu. This gives me a virtual 48GB GPU (llama.cpp ftw) to backup that 48GB of RAM. I typically see scores of at least 7-12t/…
That’s cool but 7 - 12 tps is frustrating for anything interactive.
Re: Benchmarking 15 “E-Waste” GPUs with Modern Workloads
#60Earlier quoted context omitted.
> about $80 (£60) Man, I wish I lived where you guys lived.
Same, and hope I can afford that w/$ $/t, 650w is wild to run here24/7 , would cost me 32% of my salary