4 hours ago
Hello all,
I'm in the process of setting up GPU transcoding for my Jellyfin server, but I'm running into an annoying issue at the moment. This is my current setup for reference:
Host:
VM Specs:
Jellyfin playback fails whenever transcode is required, which appears to be caused by an issue with passing through the GPU from the VM to the container. In my troubleshooting, I started by checking the output of nvidia-smi on the vm itself and inside the container:
nvidia-smi run from VM:
This gives the expected output showing the GPU is detected, and there are no active processes using it.
nvidia-smi run inside jellyfin container:
It seemed like for some reason, the GPU passthrough was not working inside docker because nvidia-smi exited before printing the GPU info. Next, I took Jellyfin out of the equation by running nvidia-smi from a simple ubuntu image:
Interestingly, this seemed to work just fine. I'm pretty sure my Jellyfin compose file is set up right, but I'll add it here regardless:
Any ideas as to what's wrong here, or anything else to look at would be greatly appreciated.
I'm in the process of setting up GPU transcoding for my Jellyfin server, but I'm running into an annoying issue at the moment. This is my current setup for reference:
Host:
- Chassis: Dell R720xd
- CPU: 2x Intel Xeon E5-2680 v2
- RAM: 320GB ECC Memory
- Hypervisor OS: Proxmox VE 9.0.11
- GPU: Nvidia Quadro P2000
VM Specs:
- CPU: 4 cores
- RAM: 8gb
- OS: Ubuntu 25.04 Server
- Nvidia Drivers: 535.274.02
- Nvidia Container Toolkit: 1.18.0-1
Jellyfin playback fails whenever transcode is required, which appears to be caused by an issue with passing through the GPU from the VM to the container. In my troubleshooting, I started by checking the output of nvidia-smi on the vm itself and inside the container:
nvidia-smi run from VM:
Code:
redacted@docker-02:~/docker/nvidia-test$ nvidia-smi
Mon Nov 10 16:13:23 2025
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.274.02 Driver Version: 535.274.02 CUDA Version: 12.2 |
|-----------------------------------------+----------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+======================+======================|
| 0 Quadro P2000 Off | 00000000:00:10.0 Off | N/A |
| 64% 51C P0 18W / 75W | 0MiB / 5120MiB | 0% Default |
| | | N/A |
+-----------------------------------------+----------------------+----------------------+
+---------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=======================================================================================|
| No running processes found |
+---------------------------------------------------------------------------------------+nvidia-smi run inside jellyfin container:
Code:
redacted@docker-02:~/docker/jellyfin$ docker exec -it jellyfin /bin/bash
I have no name!@docker-02:/$ nvidia-smi
Mon Nov 10 16:15:49 2025
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.274.02 Driver Version: 535.274.02 CUDA Version: 12.2 |
|-----------------------------------------+----------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+======================+======================|
KilledCode:
redacted@docker-02:~/docker/jellyfin$ docker run --rm --entrypoint "nvidia-smi" --runtime nvidia --gpus all ubuntu
Mon Nov 10 16:19:15 2025
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.274.02 Driver Version: 535.274.02 CUDA Version: 12.2 |
|-----------------------------------------+----------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+======================+======================|
| 0 Quadro P2000 Off | 00000000:00:10.0 Off | N/A |
| 67% 51C P0 18W / 75W | 0MiB / 5120MiB | 0% Default |
| | | N/A |
+-----------------------------------------+----------------------+----------------------+
+---------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=======================================================================================|
| No running processes found |
+---------------------------------------------------------------------------------------+Interestingly, this seemed to work just fine. I'm pretty sure my Jellyfin compose file is set up right, but I'll add it here regardless:
Code:
services:
jellyfin:
image: jellyfin/jellyfin
container_name: 'jellyfin'
user: 1000:1000
group_add: # by id as these may not exist within the container. Needed to provide permissions to the VAAPI Devices
- '107' #render
- '44' #video
# Network mode of 'host' exposes the ports on the host. This is needed for DLNA access.
network_mode: 'host'
volumes:
- jellyfin_config:/config
- jellyfin_cache:/cache
- /mnt/media-vault:/media
restart: always
runtime: nvidia
devices:
# VAAPI Devices
#- /dev/dri/renderD128:/dev/dri/render128
#- /dev/dri/card0:/dev/dri/card0
# Devices below were added during troubleshooting but don't seem to make a difference
- /dev/nvidia-caps:/dev/nvidia-caps
- /dev/nvidia0:/dev/nvidia0
- /dev/nvidiactl:/dev/nvidiactl
- /dev/nvidia-modeset:/dev/nvidia-modeset
- /dev/nvidia-uvm:/dev/nvidia-uvm
- /dev/nvidia-uvm-tools:/dev/nvidia-uvm-tools
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities: [gpu]Any ideas as to what's wrong here, or anything else to look at would be greatly appreciated.