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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
1. Blender 3D Animation rendering
2. Gaming
3. Local LLM running
If you have some good resources on this also let me know.
Is there even some coreboot or libreboot motherboard for PC that supports "high end" hardware?
As far as I know, the highest-end motherboard that supports Libreboot is an Opteron -- not Epyc, Opteron -- dual-socket server board from about a decade ago.
A key list of compatible/incompatible components to look for:
The explanations for this are pretty long, but are meant to be fairly exhaustive in order to catch most if any pitfalls one could possibly encounter.
A big one is the choice between AMD, Intel, and NVidia. I am going to leave out Intel for compute as I know little about the state it is in. For desktop and gaming usage, go with AMD or Intel. NVidia is better than it used to be, but still lags behind in proper Wayland support and the lack of in-tree kernel drivers still makes it more cumbersome to install and update on many distros whereas using an AMD or Intel GPU is fairly effortless.
For compute, NVidia is still the optimal choice for Blender, Resolve, and LLM. Though that isn't to say that modern AMD cards don't work with these tasks. For Blender and Davinci Resolve, you can get them to use RDNA+ AMD cards through ROCm + HIP, without requiring the proprietary AMD drivers. For resolve especially, there is some serious setup involved, but is made easier through this flatpak for resolve and this flatpak for rocm runtime. ML tasks depend on the software used. For instance, Pytorch has alternate versions that can make use of ROCm instead of CUDA. Tools depending on Pytorch will often have you change the Pytorch source or you may have to manually patch in the ROCm Pytorch for the tool to work correctly on an AMD card.
Additionally, I don't have performance benchmarks, but I would have to guess all of these tasks aren't as performant if compared to closely equivalent NVidia hardware currently.
One section of hardware I don't see brought up much is NICs (including the ones on the motherboard). Not all NICs play as nicely as others. Typically I will recommend getting Ethernet and Wireless network interfaces from Intel and Qualcomm over others like Realtek, Broadcom, Ralink/Mediatek. Many Realtek and Mediatek NICs are hit-or-miss and a majority of Broadcom NICs I have seen are just garbage. I have not tested AMD+Mediatek's collaboration Wi-Fi cards
so I can't say how well they work.
Bluetooth also generally sits into this category as well. Bluetooth provided by a reputable PCIe/M.2 wireless card is often much more reliable than most of the Realtek, Broadcom, Mediatek USB dongles.
This one isn't as much of a problem as it used to be. For a lot of cards that worked but had many quirks using PulseAudio (a wide variety of Realtek on-board chipsets mainly), they tend to work just fine with Pipewire. For external audio interfaces: if it is compliant to spec, it likely works just fine. Avoid those that require proprietary drivers to function.
Hard drives and SSDs are mostly fine. I would personally avoid general cheap-quality SSDs and those manufactured by Samsung. A lot of various SATA drives have various issues, though I haven't seen many new products from reputable companies actually releasing with broken behavior as documented by the kernel. If you wish to take a detailed look of devices the kernel has restricted broken functionality on, here is the list.
Additionally, drives may be one component beside the motherboard where you might actually see firmware updates for the product. Many vendors only release EXE files for Windows to update device firmware, but many nicer vendors actually publish to the LVFS. You can search if a vendor/device is supplied firmware here.
In particular, motherboards are included mainly because they have audio chipsets and network interfaces soldered and/or socketed to them. Like disks, motherboards may or may not have firmware updates available in LVFS. However, most motherboard manufacturers allow for updating the BIOS via USB stick. Some laptops I have seen only publish EXE files to do so. For most desktop boards however, one should be able to always update the motherboard BIOS fine from a Linux PC.
Some motherboards have quirky Secure Boot behavior that denies them being able to work on a Linux machine. Additionally some boards (mostly on laptops again) have either broken or adjustable power state modes. Those with adjustable allow for switching between Windows and standard-compliant modes.
Besides getting a Framework laptop 'Chromebook edition', I don't think there is much you will find for modern boards supporting coreboot or libreboot.
For your use case, this doesn't really matter. Pretty much every modern x86 CPU will work fine on Linux. One only has to hunt for device support if you are running on ARM or RiscV. Not every kernel supports every ARM or RiscV CPU or SoC.
Obviously one of the biggest factors for many new users switching to Linux is their existing peripherals that require proprietary software on Windows missing functionality or not working on Linux. Some peripherals have been reverse engineered to work on Linux (see Piper, ckb-next, OpenRazer, StreamController, OpenRGB).
Some peripherals like printers may just not work on Linux or may even work better than they ever did on Windows. For problematic printers, there is a helpful megalist on ArchWiki.
For any other peripherals, it's best to just do a quick search to see if anyone else has used it and if problems have occurred.
An elegant Linux app for the Elgato Stream Deck with support for plugins - StreamController/StreamControllerGitHub
I am going to leave out Intel for compute as I know little about the state it is in.
I forget which community it was posted in, but iirc, Intel just lost a bunch of their Linux devs (Fired? Quit? I forget). Arc had some dedicated dev time put towards it, but unless something has changed, it's likely still a hanging question as to what the future of Arc driver updates will be on Linux.
So you are probably safe to recommend people avoid Intel GPUs for now.
I am under the presumption that the current state of the Intel Arc Alchemist GPUs will likely remain about the same under Mesa even if support is dropped today by Intel. Am I mistaken in the amount of continued driver effort Intel has been putting in for the Mesa GPU drivers?
Obviously if this is true, one should probably remain wary of upcoming Battlemage GPUs.
I would be surprised if any modern network interface didn't work well with Linux. The only problems I have had is on hardware over 7 years of age. Also SSDs are all pretty good. As long as it has a good warranty you are fine. Just avoid the cheap Chinese brands.
You can totally get a random machine and then install Linux. It just works these days.
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.
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
That website is not really useful as the information is wrong or out of data
Petty much all modern hardware works with Linux. There are a few exceptions but that's very rare.
Basically the only thing that matters for LLM hosting is VRAM capacity. Hence AMD GPUs can be OK for LLM running, especially if a used 3090/P40 isn't an option for you. It works fine, and the 7900/6700 are like the only sanely priced 24GB/16GB cards out there.
I have a 3090, and it's still a giant pain with wayland, so much that I use my AMD IGP for display output and Nvidia still somehow breaks things. Hence I just do all my gaming in Windows TBH.
CPU doesn't matter for llm running, cheap out with a 12600K, 5600, 5700x3d or whatever. And the single-ccd x3d chips are still king for gaming AFAIK.
I'll also add that some frameworks and backends still require CUDA. This is improving but before you go and buy an AMD card, make sure the things you want to run will actually run on it.
For example, bitsandbytes support for non-CUDA backends is still in alpha stage. huggingface.co/docs/bitsandbyt…
Installation Guide
huggingface.coFor local LLM hosting, basically you want exllama, llama.cpp (and derivatives) and vllm, and rocm support for all of them is just fine. It's absolutely worth having a 24GB AMD card over a 16GB Nvidia one, if that's the choice.
The big sticking point I'm not sure about is flash attention for exllama/vllm, but I believe the triton branch of flash attention works fine with AMD GPUs now.
VRAM and RAM I think. Still AMD seems always slower than Nvidia for some reason for this purpose. Same for Blender benchmarks.
Ah I use my AMD GPU with Bazzite and it is wonderful.
CPU does not matter when GPU matters. Otherwise small models will do fine on CPU especially with more recent instructions for running LLMs.