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Screenshot of Demucs

// official site: github.com ↗

AUDIO & MUSIC · PRO TIER

Demucspro

Demucs is the state-of-the-art music source separation tool by Meta AI (FAIR) — splits songs into separate stems: vocals, drums, bass, and other instruments. Used by music producers, video creators, karaoke makers, podcast cleaners.

🎵 Audio & music Min 8192 MB RAM Port 7879 (http) Tier pro
// What it is

A closer look.

Demucs is the state-of-the-art music source separation tool by Meta AI (FAIR) — splits songs into separate stems: vocals, drums, bass, and other instruments. Used by music producers, video creators, karaoke makers, podcast cleaners.

The "isolate the vocals" / "remove vocals for karaoke" tool, open-source and self-hostable.

// Use cases

What it's for.

Concrete scenarios where teams pick Demucs over the SaaS alternative.

◆

Stem separation

extract vocals, drums, bass, other from any song

◈

Karaoke creation

remove vocals from licensed tracks

◇

Vocal isolation

acapella extraction for remix/study

▣

Podcast cleanup

separate background music from speech

▦

Sample mining

extract individual instruments

▩

Educational use

teach instrument identification

// Who it's for

Built for these teams.

If your team profile matches one of these, Demucs is a strong fit out of the box.

Profile A

Music producers

(acapella extraction, remix workflows)

Profile B

DJs

preparing mashups

Profile C

Video editors

cleaning audio

Profile D

Karaoke service builders

processing tracks

Profile E

Music educators

demonstrating instrument parts

Profile F

Podcasters

separating background music from speech

// Differentiators

Why teams pick Demucs.

When evaluating self-hosted options for this category, here are the dimensions on which Demucs consistently lands above the alternatives.

  • ✓Hybrid license — code MIT, weights research-only (commercial weights via separate license)
  • ✓State-of-art quality — in open stem separation
  • ✓Hybrid Transformer model — superior to LSTM-based predecessors
  • ✓Multiple model variants — quality vs speed tradeoffs
  • ✓Active research — Meta AI's continuous improvements
  • ✓Fast — 10-20× real-time on RTX 4090
// Integrations

Connects to.

The stack you'll plug Demucs into — services, protocols, and adjacent apps in the BluixApps catalog.

◇
Gradio web UI
(BluixApps custom)
◈
CLI mode
for batch
◆
Pair with
MusicGen (Demucs-extract → MusicGen-generate replacement stems)
▣
Pair with
WhisperX (vocal extract → transcribe lyrics)
▦
Output
4 stem WAV files
// Adoption & deployment

Notable users & community

  • 9k+ GitHub stars
  • Meta AI (FAIR) research backing
  • Used in commercial music tools (Karaoke services)
  • Featured in audio engineering workflows
  • Active research community

What we ship

  • Docker (pytorch CUDA 12.4 + demucs pip-installed)
  • Custom Gradio UI with model + two-stems selectors
  • Persistent volumes: models cache, input, output (4 stems WAV)
  • Port 7879 mapped
  • Install report at /root/bluixapps/demucs.txt
  • Model variant guidance
  • Use case examples (karaoke, sample mining, podcast cleanup)
  • License caveat documented (commercial restrictions on Meta-provided weights)
  • Pairing suggestions (MusicGen for replacement stems)
  • GPU pre-flight check via bluixapps_ensure_nvidia_runtime
  • Backup hook covers models + outputs
// Tips & operations

Run it properly.

Operational guidance from running this in production — what to lock down, what surprises people.

// PERFORMANCE
Model variants
// SECURITY
Two-stems mode
just vocals vs instrumental (karaoke)
// OPERATIONS
Speed
// RELIABILITY
VRAM
6 GB GPU optimal
// DEPLOYMENT
License
code MIT, weights research-only.
// SCALING
Production batch
CLI for entire albums
8192
// min ram (MB)
10
// min disk (GB)
7879
// access port
http
// protocol
pro
// bluixapps tier

Project resources

Official sitegithub.com ↗
↑