Best Free Stem Separator: Demucs vs LALAL vs Moises Compared

The best free stem separator in 2026 is Demucs if you’ll spend five minutes setting it up, LALAL.ai if you want browser convenience and the cleanest instrument split without a download, and Moises if you’re processing a folder of tracks and want a tidy UI. Those three are the only ones worth your time, and the gap between them is smaller than reviews suggest, but it’s real and it lines up with how you plan to use the output.

If you’ve tried two or three browser tools and the vocal stem keeps coming back with a ghost snare in it, the problem isn’t that “free stem separators don’t work.” It’s that you used the wrong one for that track.

The rest of this is a side-by-side on the numbers, the free-tier ceilings, and where each one breaks.

How to Read SDR (the Number That Actually Matters)

Stem separation quality is measured in Source-to-Distortion Ratio (SDR), in decibels, on the MUSDB HQ test set. That’s the academic benchmark used in the annual SiSEC source-separation challenge. Higher is better. A 1 dB jump is audible; a 2 dB jump is the difference between “usable for sampling” and “usable in a final mix.”

Key fact: On MUSDB HQ, Meta’s htdemucs model scores 9.00 dB SDR, and the fine-tuned htdemucs_ft variant scores 9.20 dB. Both numbers come from the official Demucs repository at github.com/facebookresearch/demucs.

Most browser tools don’t publish their SDR. When LALAL.ai or Moises claim “industry-leading quality,” there’s no public benchmark backing it, because their models aren’t released for academic evaluation. What you can do is run the same 30-second clip through all three, A/B the vocal stem, and trust your ears.

Demucs: The Cleanest Output, If You’ll Open a Terminal

Demucs is Meta’s open-source source-separation model. It’s free in the strongest sense: MIT-licensed, no account, no quota, runs on your own machine. The current version is Hybrid Transformer Demucs (htdemucs), with a fine-tuned variant htdemucs_ft that pushes SDR from 9.00 to 9.20 dB.

That 0.20 dB gap is small on paper. In practice, htdemucs_ft is the one to use if you have the patience: it does four passes instead of one, takes about four times as long, and noticeably cleans up cymbal bleed in the vocal stem.

You have three ways to run it:

1. Local install. pip install -U demucs, then demucs your_track.wav. On an M1 Max it processes a 3-minute song in about 30–60 seconds with htdemucs, longer with htdemucs_ft. CUDA on a recent NVIDIA card is faster.
2. Replicate. The community Demucs models on replicate.com run in the browser via API and cost roughly a cent per song. Not free at volume, but free for casual use within their trial credits.
3. Hugging Face Spaces. Several public Spaces wrap htdemucs_ft for free browser use. Quality is identical to local. Speed depends on whoever’s GPU you’re sharing.

Where Demucs wins: dense rock and metal mixes, anything with cymbals in the vocal range, and any track where you want stems good enough to release. Where it doesn’t matter: short clips for TikTok, where any of the three tools is fine.

Try it free: AI Music Generator on Studio AI — generate a fresh instrumental in about 30 seconds, then run Demucs on the result if you want to remix the stems. Start free. Generate AI Music Free →

LALAL.ai: The Cleanest Browser Tool, By a Hair

LALAL.ai is the right pick if you don’t want to install anything and you care about the instrument stems being clean, not just the vocal. Its Phoenix model handles non-vocal separation (drums, bass, electric guitar, piano, synth) better than Moises does on the same source, which the LALAL.ai team itself argues with side-by-side spectrograms in their post at lalal.ai/blog/moises-vs-lalalai — read that one with the obvious bias in mind, but the audio examples hold up if you A/B them yourself.

The free tier on LALAL gives you a small allotment of split minutes per signup before you hit the paywall. Check the live limit at lalal.ai/pricing. It’s enough to evaluate whether you like the output, not enough to process an album.

Where LALAL wins: any track where you need the non-vocal stems clean. Karaoke vocal removal where the backing instrumentation matters. Sample fishing for clean guitar or piano lines. The vocal stem alone is roughly a tie with Moises and slightly behind htdemucs_ft.

Moises: The Batch and UX Pick

Moises is the most polished interface of the three and the only one of the three with a real mobile app. Its free tier is metered in monthly minutes that reset, which makes it the only one of these three workable for any kind of recurring volume without paying. Current free-tier limits live at moises.ai/pricing.

The model is competitive on vocals. It’s a small step behind LALAL on instrument cleanliness in our A/B testing on rock and electronic material. What sets it apart is the UX around the separation: pitch shifting, tempo change, chord detection, and a clean library view that turns it into a practice tool rather than just a stem extractor.

Where Moises wins: musicians using stems for practice, anyone processing five or more tracks at once, and anyone on a phone. Where it loses: it’s the third pick if all you care about is raw separation quality.

The Verdict in One Table

If you’re picking one this week and you’ve never opened a terminal, start with LALAL.ai’s free minutes. If you have, install Demucs and never think about quotas again.

Generate Music Worth Separating

Stems are only as good as the source mix. If you’re testing stem separators on bad-sounding material, you’re testing how the model fails, not how it succeeds. Generate a clean, well-mixed instrumental on Studio AI in about 30 seconds, then run it through Demucs or LALAL to study how cleanly each tool pulls it apart.

Generate AI Music Free →

Frequently Asked Questions

Is Demucs really free?

Yes. Demucs is MIT-licensed open-source software from Meta’s FAIR lab. There’s no signup, no quota, no watermark. You install it via pip install -U demucs and run it locally, or use a free Hugging Face Space if you don’t want to install Python. The only cost is the few minutes of setup and the GPU or CPU time on your own machine.

What does SDR mean for stem separation?

Source-to-Distortion Ratio measures how cleanly a separated stem matches the original isolated source, in decibels. It’s the standard academic metric, evaluated on the MUSDB HQ test set. Higher is better. The current best published number for an open model is htdemucs_ft at 9.20 dB; below 6 dB you can clearly hear leakage; above 9 dB the artifacts are subtle.

Which free stem separator works best for vocals on hip-hop?

All three are roughly equivalent on hip-hop vocals because the vocal sits clearly above the beat in the mix. LALAL.ai is the fastest path if you’re doing it once. Moises is the better choice if you’re isolating vocals from a folder of beats. Demucs htdemucs_ft will give you the cleanest acapella if you’re publishing the result.

Can I use stem separation on a copyrighted track?

You can run it; what you do with the output is the legal question. Stem separation produces a derivative work of the original recording, so commercial use without a license is the same infringement as sampling without clearance. For practice, transcription, and learning, it’s fair use territory in most jurisdictions. For release, you need rights to the source.

Why does the “other” stem always sound the worst?

Because it’s a catch-all. The four-stem models are trained on vocals, drums, bass, and “everything else.” Anything the model couldn’t confidently assign to the first three lands here, and so does most of the leakage. If you need a clean guitar or piano specifically, LALAL’s instrument-specific Phoenix splits are better than running a four-stem model and digging through the “other” stem.

Is there a free stem separator with no upload limit?

Demucs, run locally. Every browser-based tool — LALAL.ai, Moises, every clone of them — meters the free tier somehow, because they’re paying for GPU time on your behalf. Demucs runs on your own hardware, so the only limit is your disk space and patience. That’s the real reason it wins on cost over any time horizon longer than a week.