The current state of hardware acceleration support in FFmpeg can be checked on the rpi-ffmpeg repository. Jellyfin will fallback to software de/encoding for those usecases. This decision was made because Raspberry Pi is currently migrating to a V4L2 based hardware acceleration, which is already available in Jellyfin but does not support all features other hardware acceleration methods provide due to lacking support in FFmpeg. Video Scaling & Format conversion (optional)Īs of Jellyfin 10.8 hardware acceleration on Raspberry Pi via OpenMAX OMX was dropped and is no longer available. The transcoding pipeline usually has multiple stages, which can be simplified to:

Raspberry Pi Video4Linux2 (V4L2, Linux only) Intel/AMD Video Acceleration API (VA-API, Linux only) The supported and validated video hardware acceleration (HWA) methods are: It enables the Jellyfin server to access the fixed-function video codecs, video processors and GPGPU computing interfaces provided by vendor of the installed GPU and the operating system. The Jellyfin server uses a modified version of FFmpeg as its transcoder, namely jellyfin-ffmpeg. The Jellyfin server can offload on the fly video transcoding by utilizing an integrated or discrete graphics card ( GPU) suitable to accelerate this workloads very efficiently without straining your CPU. | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. This command is also useful if you want to check performance metrics of the sudo nvidia-smi To confirm that the driver was installed correctly and that your GPU is being recognized, run nvidia-smi. Kernel modules: nvidiafb, nouveau, nvidia_375_drm, nvidia_375Ġ1:00.1 Audio device : NVIDIA Corporation Device (rev a1) To find out if your GPU is installed properly and working run the following sudo lspci -nnk | grep -i nvidiaĠ1:00.0 VGA compatible controller : NVIDIA Corporation Device (rev a1)

Ubuntu nvidia