nvidia-patch VS jellyfin-tizen

This can be patched out. https://github.com/keylase/nvidia-patch

NVIDIA Corporation GA106 [GeForce RTX 3060] and I applied the patch here https://github.com/keylase/nvidia-patch

> CUDA, and pretty much all optimization(hacks) done to run games better

And arbitrary limitations implemented at the driver level to force you to purchase their enterprise GPUs, see https://github.com/keylase/nvidia-patch#nvenc-and-nvfbc-patc...

Nvidia has no motivation to make a consumer card with lots of VRAM, that's basically the only (relevant) separator between the GeForce family and the Quadro lineup.

There are restrictions on NVENC streams with consumer cards, but that has been a solved problem for a while [0].

If they were to make a consumer card with more VRAM, it would immediately undercut their own Quadro/Tesla lineup, which cost substantially more. I don't see a reason for them to do it.

0: https://github.com/keylase/nvidia-patch

I have never had to do the session limit bump thing from the last link. I have a 3090 as well and simply did the initial unlock, which worked fine. I would reinstall fresh drivers from Nvidia, making sure you install the newest one that is supported by the unlock tool (536.40 as of this post, the GitHub for the patch has links to the drivers - https://github.com/keylase/nvidia-patch/tree/master/win)

Aren't these Quadro versions. The patch here. https://github.com/keylase/nvidia-patch supports Quadro versions of you click on the win clickable.

Second, the GPU. The GPU is probably as important as the CPU, and in some cases more important, and when we talk about GPUs we will primarily talk about Nvidia GPUs as they are officialy supported by the Plex team. NVIDIA GPUs are important for Plex hardware transcoding due to their dedicated video encoding/decoding units, superior performance, wide codec support, improved video quality, reduced CPU load, power efficiency. They offer a powerful hardware acceleration solution that can greatly enhance the transcoding capabilities of a Plex server. It's also important to note that Nvidia GPUs require a patch to unlock the number of HW transcoding streams. Dedicated GPUs are large pieces of hardware and have their place in desktop PCs. However, they can also be used with mini-PCs by using an external GPU enclosure.

As there's no NVENC patch available (yet) for the Beta driver branch - referring to this one: https://github.com/keylase/nvidia-patch - which can lift the limits of HW transcoding, I was now wondering a little, as I can see 5 (hw) streams on Plex, which actually shouldn't/cannot be the case no?

I haven’t done this yet but there is a patch on GitHub that removes the limitation for consumer GPUs. Makes lower end cards more attractive for this type of work

I cannot help you with this, but this is what I found.

The official repo: https://github.com/jellyfin/jellyfin-tizen

Following this github link.

This is the github repository link I'm following: (https://github.com/jellyfin/jellyfin-tizen/blob/a8629f095dc8ef25878796f549defbb306978246/README.md)

If you're actually going to use the extra features of Plex/Jellyfin over a pure media player like Kodi, generally you would install the sever on a headless box, then install the client on your TV or connected media player. Plex is usually a single click app install on most Samsung TVs. Jellyfin might take a bit more work.

there is a Tizen client (https://github.com/jellyfin/jellyfin-tizen) but it isn't on the app store so you need to install it with dev mode which isn't easy for the average Joe

The app version is just whatever git HEAD was when I built it, d23ca24. The server version is 10.8.9-1 on a RPi 2 installed via apt.

It's unfortunate but you can compile and deploy an app for Samsung: https://github.com/jellyfin/jellyfin-tizen