this post was submitted on 30 Apr 2025
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These are great for certain use cases, but there are areas where volume is critical for economy of scale and we have no equivalent.
Like with my disability and ergonomic needs I went looking for a laptop with an AI capable GPU. Also because building hardware is such a garbage marketing scam to navigate. I got a late- 16GB GPU model for $2k when all I could buy was a 12GB S76 for $3k5 or 16GB for $4k5+ and it had a 14k9 Intel with C4-roulette bomb built in.
We are at a stage where it is insane that gaming is even relevant to GPU specs. The die used in almost all of these GPUs are not only capable of handing a lot more RAM, but the support for more RAM is actually already in the firmware and only configured by soldering the correct chips and changing a configuration resistor on the PCB. Most chips are more than capable of addressing the maximum memory that was available in the series. There are people posting on YT demonstrating this swap on multiple Nvidia cards. So either we must be able to buy a GPU with replaceable memory or hardware should be sold with the option for maximum. Gamers have no use for this, but it is super important for AI stuff. Like I was looking at getting some old P40 Tesla GPUs just because they have 24GB of ram but it would take 8 of them to have as much compute as my current single 16GB GPU on a laptop! I would love to buy a similar machine with something like a 48GB GPU in a 3090 or 4090 like class and with Tesla hardware that cannot be used for gaming. That absolutely cannot be some super rich, I-made-up-a-price boutique retailer bullshit. The existing hardware already supports this where something like a 5070 and 5060 are more than capable of shipping with 32GB of RAM attached. It is not super niche or stupid expensive to use chips that are a few dollars more each when the bulk of the cost is the same and already being spent. Sure my Tesla GPU laptop dream is edgy, but shipping a 32GB 5060 at economy of scale ~$2k is not. Even Nvidia should start classing dice and putting out AI specific specs if the bad blocks in a die permit just killing the ray tracing junk but can still do tensor math. These kinds of things are in the near future of possibility, but I don't see anyone in the Linux space being particularly edgy and leading by offering something great. They are acting like boutique retail and charging premiums or offering mundane hardware for tried and true use cases.
Anyways, I wanted to support S76 but paying twice as much, and when they do not open source their bootloader, it was a solid no for me. Fortunately https://linux-hardware.org/ exists and shows the kernel log and what works and does not work for almost all hardware that exists. Do a scan of your stuff to help others too, especially if you use esoteric stuff, unusual distros, or find some workaround to get hardware working when it did not work before. We don't have very good economy of scale with edge case and enthusiast hardware, but this is a way around that.