I see the raise of popularity of Linux laptops so the hardware compatibility is ready out of the box. However I wonder how would I build PC right know that has budget - high end specification. For now I’m thinking
- Case: does not matter
- Fans: does not matter
- PSU: does not matter
- RAM: does not matter I guess?
- Disks: does not matter I guess?
- CPU: AMD / Intel - does not matter but I would prefer AMD
- GPU: AMD / Intel / Nvidia - for gaming and Wayland - AMD, for AI, ML, CUDA and other first supported technologies - Nvidia.
And now the most confusing part for me - motherboard… Is there even some coreboot or libreboot motherboard for PC that supports “high end” hardware?
Let’s just say also a purpose of this Linux PC. Choose any of these
- Blender 3D Animation rendering
- Gaming
- Local LLM running
If you have some good resources on this also let me know.
You need to use intel/nvidia.
You might be able to get away with amd instead of intel, but nvenc and cuda support is a non negotiable thing for your use case.
You will not encounter any problems as long as you don’t run Wayland.
Any motherboard is fine. You don’t need coreboot support to run Linux.
Just a point on Wayland - I have an nvidia GPU and have been on Wayland for a couple months now (KDE Plasma), and its been entirely problem free and I actually forgot I switched from X11 to Wayland.
Blender has support for Wayland now too.
I do a lot of gaming and development - ever since Nvidia made those changes for Wayland support and KDE added that explicit sync stuff its been great. Before all of that though I had heaps of issues with flickering and just general usability.
Wayland actually fixed a number of issues for me, like stuttering when notifications appear, and jankyness in resizing windows.
As a non-Wayland user, I’m glad it’s coming along.
You can absolutely use an AMD card for LLMs. You can even use the CPU if you don’t mind it being slower.
If this person is a AI researcher doing lots of LLM work it might be different but somehow I think they are just a casual user that asks questions
Both blender and every llm library I’m aware of work better and have broader support with nvidia hardware.
That’s two out of three of the ops use cases.
Gaming, the third use case, is perfectly fine using an nvidia card.
There’s nothing wrong with amd video cards, but for this user, in this case, they’re not the choice I would recommend.
Especially if they’re just a normal person who asks questions because it’s much, much more likely that someone who uses blender or llms will be able to answer their questions and address any issues related to hardware because people using blender and llm are broadly using nvidia cards.
The problem is that Nvidia cards also such under Linux. Sure it may work in some configurations but with a Intel or AMD GPU it works without fiddling around. As long as you have a new enough kernel it is a good experience.
I don’t think that’s relevant.
To employ a car metaphor, I own a small Japanese sedan. I’ve installed an aftermarket tow hitch and have used it to haul small trailers. I have a pair of toolboxes in the trunk and I live up a road that after recent events would be considered a technical driving course. I’m able to get home just fine in my small, low clearance car with a four cylinder engine and touring tires.
If a person asked me: “what vehicle should I get for towing, working in trades and off roading on the weekend?”, I’d absolutely never suggest a Honda accord.
While the experience of owning a diesel truck is more complex and requires some fiddling around, for example, remembering to use the green pump, understanding when to use the fuel cutoff switch, using a block heater when it’s cold outside, saving up more money for repairs and generally actually operating the vehicle differently under almost any comparable conditions, it’s the right tool for the job at hand and dealing with those differences is part and parcel not just of handling the tool, but completing the job.
Interesting you exclude AMD.
Any? I was thinking of MSI or Asus motherboards.
I don’t know of any msi or asus boards with problems. Of course, I rejected coreboot as a requirement so that plays into it.
My personal experience is: don’t overclock and everything will run fine for at least ten years.
Blender works faster with nvidia and it’s been the optimal hardware for maybe two decades now. There’s just so much support and knowledge out there for getting every feature in the tool working with it that I couldn’t in good faith recommend a person use amd cards to have a slightly nicer Wayland experience or a little better deal.
If you’re only doing llm text work then a case could be made for a non cuda (non-nvidia) accelerator. Of course at that point you’d be better served by one of those coral doodads.
Were you only doing text based ml work or was there image recognition/diffusion/whatever in there too?