Well being able to figure out 1 complex math solution per day vs 1 complex solution per 1.5 days for the person who just has to work on the problem for longer is balloons a lot over the long term.
Like how the average calorie burning difference between people is only 400 per day out of ~2000, but over a month that is like 1.5kg difference of mass burned which is 18kg per year.
But I don’t know if I am interpreting the result you said correctly.
It is the Mac of network hardware in my corporate - entered experience.
It is aesthetic hardware, marketing, and everything software related looks polished on the surface, but is buggy (particularly their access which is the worst thing to be buggy) with the least possible configurability, completely obscured debugging resources, and proprietary ways to make you reliant on their support services.
That being said, I am still using them because I got a 30€ UAP-AC-SHD from my company’s old stock when we switched to Cisco hardware. And their cloud gateway ultra is a good value. My whole house setup with prosumer hardware will be 140€ and where my internet comes in is the worst place in the house to put a wireless router.
Are you absolutely sure that you have the i915 firmware installed and enabled?
If you have gone through these steps of adding the modules: https://jellyfin.org/docs/general/administration/hardware-acceleration/intel/#low-power-encoding
and it doesn’t work, you may have to manually download the git linux firmware library, extract the i915 folder and place it in your firmware folder.
That is how I got jellyfin working on my A380 after pulling my hair out about it.
Please check and post your dmesg starting up.
You should see GUC and HUC enabling.
This is a good way to do it.
I went one smaller with the Node 304 which only can do 4 HDDs with a GPU inserted. Going used for consumer desktop CPU is the most powerful play for the money I think.
This is a good path forward OP for a pretty powerful server