Their answer:

> If you are interested in how well we do compared to demucs in particular, we can use the MUSDB18 dataset since that is the domain that demucs is trained to work well on. There our net win rate against demucs is ~17%, meaning we do perform better on the MUSDB18 test set. There are actually stronger competitors on both this domain and our "in-the-wild" instrument stem separation domain that we built for SAM Audio Bench, but we either match or beat all of the ones we tested (AudioShake, LalalAI, MoisesAI, etc.)

So ~20% better than demucs, better than the ones they tested, but the acknowledge there are better models out there even today. So not sure "competes against SOTA models" is right, but "getting close to compete against SOTA models" might be more accurate.

I suppose that depends on the use case.

For mash-ups specifically, using yt-dlp to download music and split into stems with Demucs, using the UVR frontend, before importing into a DAW is effortless. The catch is that you can't expect to get OK-ish separation on anything other than vocals and "other", which really isn't a problem for mash-ups.

https://github.com/Anjok07/ultimatevocalremovergui

If you're already in the Ableton ecosystem, their newly released stem separation is actually very good, at least for the small amount of testing I've done so far. Much better than demucs, which shouldn't come as a surprise I suppose.

I use RipX DAW personally. It very cleanly seperates vocals, guitar, bass, and drums.