
Light and fast
Light enough to run at scale on ordinary CPUs, which is what makes catalogue-sized batch jobs affordable.
Deezer
The separation tool that made stem splitting ordinary.
In short
Figures verified 2026-08-10. This field moves quickly — re-check before relying on them.
Spleeter's historical importance is hard to overstate: it made stem separation a thing anyone could do, and an entire generation of remix and karaoke tools was built on it. Its enduring advantage is efficiency. It is light enough to run on ordinary hardware, fast enough to process a large catalogue without a GPU budget, and simple enough to reason about when something goes wrong. For batch work across thousands of files where good-enough separation is genuinely good enough, that profile still wins. On quality it has been clearly overtaken. Demucs produces cleaner separation with better transient preservation, and the gap is audible on any material more complex than a sparse pop mix. Choose Spleeter for throughput and simplicity, Demucs when the stems have to survive close listening.
Strengths

Light enough to run at scale on ordinary CPUs, which is what makes catalogue-sized batch jobs affordable.

It made separation ordinary, and the resulting ecosystem of tutorials and wrappers is still the largest of any separation tool.

A simple, well-understood pipeline is easy to debug when a file fails, which matters more in production than peak quality does.
How it compares
Spleeter is Deezer's open source source-separation library, splitting a mix into two, four or five stems. It is fast and light on resources, and has been superseded on quality by Demucs while remaining useful for batch processing.
Compare with MusicGenerate
Searched as spleeter, deezer spleeter, spleeter github and free stem separation. It made separation ordinary, which is why the ecosystem around it is still the largest.
For batch work across thousands of files where good-enough separation is genuinely good enough, its efficiency still wins. For stems that must survive close listening, use Demucs.
Two, four or five, depending on the model you pick. There is very little else to configure, which is precisely the appeal for batch deployment.
It is a lighter model that runs happily on ordinary CPUs, which is what makes catalogue-sized jobs affordable without a GPU budget.
Yes, open source under a permissive licence, so deploying it is unproblematic. The licence covers the software and grants no rights over the recordings you process.
Development has slowed considerably, and Demucs has taken over as the actively developed reference. Spleeter still runs fine, which is why it persists in batch pipelines.
Two if you only need vocals and instrumental, four for drums and bass separately. More stems means more chances for the algorithm to misattribute sound.
More models
Models and platforms we track, compared on capability and licence.