stemdeckapp/stemdeck

v0.8.0-alpha.4 Feature

This release adds 2 notable features for engineering teams evaluating rollout.

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✓ No known CVEs patched

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✓ No known CVEs patched in this version

Affected surfaces

breaking_upgrade

Summary

AI summary

Updates Artifact scan, Installing, and Artifact build across a mixed release.

Full changelog

[!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
Upgrading from alpha.9 or earlier? If after installing you still see an old version or are missing recent features, clear the cached runtime once and relaunch:
rm -rf ~/Library/Application\ Support/StemDeck/runtime ~/Library/Application\ Support/StemDeck/runtime.old

What's new in 0.8.0 Alpha 4

Blackwell GPU fix (RTX 5000 series, Windows)

RTX 5000 series users on the NVIDIA build were running stem separation on CPU instead of GPU. The CUDA setup was completing but the kernel verification step was silently failing, triggering a CPU fallback with no visible warning.

Upgraded the bundled PyTorch for NVIDIA Blackwell (sm_120) from 2.7.1+cu128 to 2.8.0+cu128, which ships complete sm_120 kernels. This is the most likely root cause of the verification failure on RTX 5000 hardware.
CUDA verification failures are now logged to logs/setup.log in the StemDeck data folder, making it possible to diagnose GPU setup problems.
When a GPU is detected but CUDA setup fails, the app now shows a visible error during setup instead of a status line that was easy to miss.

Installing

macOS: drop the .app into Applications and launch (run the xattr command above first).
Windows: unzip the downloaded .zip, then run StemDeck.exe from the extracted folder.
Linux: download the .tar.gz for your hardware, extract it, and run ./StemDeck. Install the WebKitGTK + GTK runtime prerequisites first (FFmpeg is fetched automatically on first launch):
```
sudo apt install libwebkit2gtk-4.1-0 libgtk-3-0
```
The NVIDIA build additionally needs a working NVIDIA driver such that nvidia-smi reports your GPU (the CUDA runtime itself is bundled -- no separate CUDA toolkit install needed). If you have no NVIDIA GPU, use the CPU-only tarball.

Artifact scan

Windows portable packages (CPU + NVIDIA) scanned with ClamAV in CI before upload.
Linux portable packages (CPU + NVIDIA) scanned with ClamAV in CI before upload.

Artifact build

macOS arm64 and x64 DMGs and runtime packs built and inspected on a macOS runner before upload.
Windows portable ZIPs (CPU + NVIDIA) built on a Windows runner.
Linux portable tarballs (CPU + NVIDIA) built on a Linux runner.