Important
macOS first launch (no code signing yet). After dragging StemDeck to Applications, clear the Gatekeeper quarantine flag or macOS will say the app is damaged:
xattr -dr com.apple.quarantine /Applications/StemDeck.app
Optional: start from a clean slate. To reproduce a true first-run experience, open each path in Finder via the Go menu, then Go to Folder (Shift+Cmd+G), and move the folders to Trash:
~/Library/Application Support/StemDeck~/Library/WebKit/app.stemdeck.desktop~/Library/Caches/stemdeck~/Library/Caches/app.stemdeck.desktop
You can also delete ~/Library/Preferences/app.stemdeck.desktop.plist the same way. This is optional; the app will work without it.
What's new in 0.8.0 Alpha 14
A Linux fix release. The NVIDIA build for Linux could not start at all in Alpha 13 — this release makes it work.
The Linux NVIDIA build now starts
In Alpha 13, StemDeck-Linux-x64.NVIDIA failed setup with "Setup could not complete — backend did not become healthy within 90 seconds." It affected every machine, not just some GPUs.
The cause: on first launch the NVIDIA build downloads the CUDA version of PyTorch matched to your GPU, but it was fetching PyTorch without the CUDA runtime libraries it needs to load. Starting the audio engine then failed on a missing libcublas, and the app never got past setup. StemDeck now installs those libraries alongside PyTorch.
If you hit this in Alpha 13, download the Alpha 14 tarball and extract it to a fresh folder — your library and settings live outside the app folder and are not affected.
Expect a large one-time download. The first time you launch the Linux NVIDIA build on a GPU machine, it fetches the CUDA runtime (roughly 2.5 GB). This happens once per install; later launches start immediately. This is the same tradeoff the Windows NVIDIA build already makes, and it keeps the download small for everyone else.
A failed GPU setup no longer breaks the app
If CUDA can't be set up or verified on your machine — old driver, unsupported card, interrupted download — StemDeck now puts the CPU version of PyTorch back and opens normally on CPU. Previously a half-installed GPU setup could leave the app unable to start at all, on every subsequent launch.
Security updates
yt-dlpupdated to 2026.7.4 (CVE-2026-55404).
macOS and Windows
No functional changes in this release — only the dependency updates above. If Alpha 13 is working for you on macOS or Windows, there is no need to update.
Installing
- macOS: drop the
.appinto Applications and launch (run thexattrcommand above first). - Windows: unzip the downloaded
.zip, then runStemDeck.exefrom the extracted folder. For GPU acceleration, use the NVIDIA zip and make surenvidia-smireports your GPU; the CPU zip runs anywhere. - Linux: download the
.tar.gzfor your hardware, extract it, and run./StemDeck. Install the WebKitGTK + GTK runtime prerequisites first (FFmpeg is fetched automatically on first launch):
The NVIDIA build additionally needs a working NVIDIA driver such thatsudo apt install libwebkit2gtk-4.1-0 libgtk-3-0nvidia-smireports your GPU. You do not need to install the CUDA toolkit — StemDeck downloads the CUDA runtime it needs on first launch (see the note about the one-time download above). If you have no NVIDIA GPU, use the CPU-only tarball. - Docker / Unraid: install "StemDeck" from Unraid Community Applications, or pull
ghcr.io/stemdeckapp/stemdeck:edgeand map port 8000 plus the/app/jobsand/cachevolumes. Add--runtime=nvidiafor GPU acceleration. See the README for the fulldocker runcommand.