Open-Source AI Music Models
The open-source AI music models you can run yourself — MusicGen, Stable Audio Open, ACE-Step, YuE, Riffusion, Magenta and RAVE — with their types, licences and hardware needs.
Models you can run yourself
Open models let you generate music without a subscription, keep your data private, and build them into your own tools — subject to each model's licence. Here are the ones worth knowing, all runnable in Python.
| Model | Type | Licence | Vocals |
|---|---|---|---|
| MusicGen | Text / melody → instrumental | Open, non-commercial weights | No |
| Stable Audio Open | Text → audio | Open (community licence) | No |
| Riffusion | Text → music | MIT (original) | Yes (web) |
| YuE | Lyrics → song | Open | Yes |
| ACE-Step | Text → music | Open (Apache-2.0) | Yes |
| Magenta | Symbolic / MIDI | Open (Apache-2.0) | No |
| RAVE | Neural synthesis | Open, non-commercial | No |
The short version
- MusicGen — the most established open instrumental model; great quality, but non-commercial weights. Tutorial →
- Stable Audio Open — short audio, loops and SFX; community licence. Tutorial →
- ACE-Step — fast, Apache-2.0, does full songs; among the most product-friendly licences here.
- YuE — open lyrics-to-song with vocals (Apache-2.0, weights included), the closest open answer to Suno.
- Riffusion — the original open, spectrogram-based approach.
- Magenta and RAVE — symbolic/MIDI generation and neural timbre transfer, respectively.
Hardware. Most of these want a CUDA GPU with 8 GB+ of VRAM for comfortable use; the smallest MusicGen model will run (slowly) on CPU. Full-song models like YuE are the most demanding.
Not sure open is right for you? Compare with the web apps on the best AI music generators page.