deezer/spleeter

Health v2 · maintenance only

Adoption not part of the score

28402 stars · 3060 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

Spleeter is Deezer's music source separation library with pretrained TensorFlow models that splits audio into stems (vocals, drums, bass, piano, other). It works as a CLI tool, a Python library, or a Docker image, and runs up to 100x faster than real-time on GPU.

Use cases

• separate vocals from a song's instrumental
• extract drums and bass stems from an mp3
• make a karaoke/acapella track from any song
• split audio into 2, 4, or 5 stems
• train a custom source separation model on my own dataset
• batch process a music library into stems

When to choose

• you need fast, pretrained music stem separation without training your own model
• you want a CLI or Python API for separating vocals/accompaniment
• you have a GPU and need faster-than-real-time separation

When to avoid

• you need real-time live separation in a production audio pipeline
• you need separation of stems beyond the pretrained models (e.g. guitar-only) without your own training data
• you need a maintained, actively developed solution - the project is largely in maintenance mode

Facets

library · maturity maintenance

audio-processing machine-learning deep-learning cli machine-learning audio media python cli cross-platform source-separation stem-separation pretrained-models tensorflow music karaoke deezer audio docker gpu

Member repositories

For agents

markdown · JSON · MCP: product_card(name="deezer/spleeter")