Skip to content
SPECIFICTION
Get listed

Open-Unmix vs Pymss

Open-Unmix

github.com

Pymss

pymss.net

Side by side

FigureOpen-UnmixPymss
Price fromFreeFree
Free planYesYes
Free trial——
Open source—Yes
Web—Yes
WindowsYesYes
macOSYesYes
LinuxYesYes
iOS—Yes
Android—Yes
API—Yes
Self-hostedYesYes
Plans published11
Spec score · Stem Separation Software7.8 (#12)8.6 (#5)
IntegrationsPre-trained models can be loaded from Python or through torch.hub, and a Google Colab notebook offers online experimentation without local setup.The project provides ComfyUI custom nodes and a VST3 ARA plugin for use in DAWs.
PurposeOpen-Unmix is a PyTorch reference implementation for music source separation aimed at researchers, audio engineers, and artists.Pymss is an open source music source separation toolchain that separates vocals, drums, bass, and other stems on the user's machine.
SupportThe project directs users to GitHub issues, Gitter chat, and Google Groups for technical help and support.The project points users to GitHub documentation and an issue tracker, and its Studio README lists a QQ group for Chinese beta testing, bug reports, and community discussion.

Plans

Open-Unmix

  • Open-UnmixFree

Open-Unmix pricing →

Pymss

  • PymssFree

Pymss pricing →

In their own words

Open-Unmix

Open-Unmix is a PyTorch reference implementation for music source separation, aimed at researchers, audio engineers, and artists. Its ready-to-use models split pop music into vocals, drums, bass, and other instruments; a separate model, umxse, is for speech enhancement and was trained on the 28-speaker Voicebank+DEMAND corpus. Pre-trained choices include umxl, umxhq, umx, and umxse, with spectrogram variants also available. Each source model uses a three-layer bidirectional LSTM, a design the project says cannot run online or in real time. The code supports reproducing results, developing architectures, and adding data, while training is documented separately from the package. Install through pip or use the Docker container; pre-trained models can be loaded in Python or through torch.hub, and a Colab notebook supports online experimentation without local setup. The command line handles WAV, FLAC, and OGG, not MP3; stempeg can extend formats, including STEMS export. The software is MIT-licensed; umxl weights are non-commercial under CC BY-NC-SA 4.0.

Visit github.com

Pymss

Pymss is an open-source music source-separation toolchain that runs on the user's own machine and separates audio into vocals, drums, bass, and other stems. Its Studio desktop workspace handles model management, batch jobs, and stem editing. Users can import files or folders, choose a downloaded model, configure inference, and queue work. Studio can browse, download, resume, and delete model files, with storage cleanup controls. Waveform previews, mix controls, saved projects, and stem export support work on the results. Pymss can chain models so each workflow step uses the preceding step's output. The inference package lists WAV, FLAC, MP3, M4A, AAC, Opus, Vorbis, and Ogg output. Other components include ComfyUI custom nodes, a VST3 ARA plugin for compatible DAWs, and a browser interface bundled with the server. The ARA plugin provides per-stem mute and solo controls; its README gives Reaper and Studio One as host examples. The repositories have separate licenses: Studio is listed under AGPL-3.0 and the inference package under MIT. Studio remains at an early development stage, and changes between versions may break things.

Visit pymss.net