Summary of "Transcoding with an Nvidia GPU & Unlocking it for Maximum Streams in Plex, Emby & Jellyfin"

Goal

Use an NVIDIA GPU for hardware transcoding on Unraid 6.9+ for:

Plex
Emby (Jellyfin-compatible setup via NVIDIA/encoding stack)
Jellyfin

For users without Quadro cards, the video explains how to remove NVIDIA’s consumer “multiple session” limitations—described as “unlocking” the card to enable maximum streams.

Key concepts / constraints discussed

1) NVIDIA “multiple sessions” limitation + Quadro recommendations

Common advice: use Quadro GPUs since they can transcode multiple streams.

The presenter argues this is not strictly necessary. Cheaper NVIDIA consumer GPUs can achieve similar behavior by:

Installing appropriate drivers
Applying an “unlock” method

2) EULA / compliance debate and “VM passthrough” context

The video covers:

NVIDIA restrictions for GPU use in VMs (mentions Error 43).
Unraid has patches that reduce detection/driver disabling during GPU passthrough.
The presenter claims these VM patches don’t modify NVIDIA driver code, but warns that unlocking for multi-transcode may violate NVIDIA’s driver EULA.

Viewer discretion advised.

Installation & setup guide (Unraid 6.9+)

Step A — Update Unraid to 6.9+ (if needed)

Go to Tools → Update OS
Install the Stable branch (video notes stable released Feb 22, 2021)
Reboot after updating

Step B — Install NVIDIA driver support on Unraid

Open the Apps tab
Search for “nvidia”
Install the NVIDIA plugin
After installation:
- Stop and restart Docker to ensure drivers are ready

Step C — Install GPU monitoring

Install “GPU Statistics” plugin and set:

Vendor = NVIDIA
Select the specific GPU (if multiple GPUs exist)

Docker container setups for transcoding

Common container requirements

Use NVIDIA-enabled containers (examples shown):

LinuxServer Plex
LinuxServer Emby
LinuxServer Jellyfin

For each container’s template:

Map media paths (movies/tv/music)
Set NVIDIA_VISIBLE_DEVICES to the GPU ID
Add container parameter: --runtime=nvidia
Switch to Advanced view to edit Extra parameters

Plex (hardware transcoding verification)

Install LinuxServer Plex container
Configure:
- NVIDIA GPU ID
- --runtime=nvidia
In Plex settings, ensure hardware accelerated video encoding is enabled by checking:
- “Use hardware acceleration when available”

Requirement highlighted:

Hardware transcoding requires a Plex subscription / Plex Pass

Testing / verification:

Force a transcode (e.g., “Convert to 720p”)
Check Plex Dashboard for HW (hardware encoding)
Confirm on Unraid using GPU Statistics (video later indicates multiple concurrent transcodes, e.g., 3)

Emby (Emby Premier requirement + NVENC check)

Install LinuxServer Emby container (default branch used in the video)
Enable hardware acceleration when available in Emby settings

Requirement highlighted:

Emby Premiere account (not just the free tier) for hardware transcoding

Testing / verification:

Force a transcode to 720p
In Emby UI, verify details show:
- Transcoding steps like H.265 → H.264
- Use of NVENC (video shows “nvidia encode decode” / H.265 to H.264 using NVENC)

Monitoring:

Unraid GPU Statistics shows activity
The presenter notes minor UI confusion about whether Emby appears correctly as an “active app,” though GPU usage is still indicated

Jellyfin (free, config + transcoding type)

Install LinuxServer Jellyfin container
Configure:
- NVIDIA GPU ID
- --runtime=nvidia

Jellyfin-specific settings:

Admin Dashboard → Transcoding
- Set Hardware acceleration to something other than “none”
- Select transcoding backend NVENC
- (Video mentions choosing from multiple options under that section, described as selecting “top five”)

Testing / verification:

Force a transcode (e.g., “Conan the Barbarian” to 720p)
Verification relies heavily on Unraid GPU Statistics, since the Jellyfin UI text is not clearly readable in the video

Key point:

Unlike Plex/Emby, Jellyfin setup is presented as not requiring a paid key

Multi-container / multi-stream validation

The video claims the NVIDIA GPU can handle multiple containers simultaneously.

Demonstration:

Run Jellyfin + Plex + Emby concurrently with multiple transcodes

Confirmation:

GPU Statistics shows three processes

Note:

Emby may have a minor display/UX issue where activity doesn’t appear as expected in the “active app” view, but hardware usage still appears confirmed via GPU stats.

“Unlocking” NVIDIA for more concurrent transcodes (spike-cushion analogy)

After transcoding demos, the presenter demonstrates an automated patch workflow:

Stop all GPU-using containers
Install User Scripts plugin
Create a script named “unlock nvidia”
Paste a patch script fetched from a link in the description
Schedule it to run at array start
Run it immediately to patch/unlock the driver

Analogy: “spike cushions” are used to explain the concept of bypassing NVIDIA limitations by effectively changing what the system allows.

This is also tied back to the earlier discussion about EULA.

Main speakers / sources

Primary speaker

The video author/presenter (“hi there guys…”), who installs/configures everything and discusses Plex/Emby/Jellyfin setup and the unlocking approach.