Comparison · Open source vs API

Source Separation API vs Self-Hosted Demucs

Demucs is the open-source quality standard, and self-hosting it is a real engineering project. This is the honest cost comparison — quality, GPUs, ops, and when each choice makes sense.

DemucsSource separationComparison

What self-hosting Demucs really is

Demucs/HTDemucs is an excellent model. Running it in production means: GPU capacity, CUDA/PyTorch environment management, model checkpoints, a job queue with retries, monitoring, and keeping the model current. Each of those is a project; together they are a team.

Side by side

Self-hosted Demucsmlslabs API
QualityState of the artSame model family, per-mode tuning
GPU costFixed monthly, idle included$0 — per minute of audio
ThroughputOne GPU lane per queueElastic parallel workers
Ops burdenQueue, retries, monitoring, updatesNone
Data controlFully on-premObject storage in/out
BatchYou build itNative + webhooks

The quality question

Both use HTDemucs-class models; quality differences come from tuning, not the base engine. Our modes are tuned per workload (music vs speech), which is the variable that matters most for real results. A/B on your own audio before choosing.

Decision rules

  • Data must never leave your environment → self-host
  • Existing idle GPU fleet → self-host
  • Product feature, variable volume → API
  • No GPU ops team → API
  • Bursty batch jobs (karaoke, remix, catalog) → API

FAQ

Common questions

Is the API as good as Demucs?

Same model family with per-mode tuning — run a blind A/B on your files. Most teams find API quality at least equal, with far less operations.

What does a self-hosted GPU cost?

A rented GPU for continuous separation runs hundreds per month before your engineering time. The API bills per minute of audio, so idle costs zero.

Can I process a full catalog?

Yes — that is the API's designed workload: submit N jobs, collect N webhooks, pay per audio minute.