Stable Audio 3
About
Stable Audio 3 is a family of fast latent diffusion models (small, medium, large) for variable-length audio generation and editing. Since our models can generate several minutes of audio, variable-length generations are key to avoid the cost of producing full-length generations for short sounds. We also support inpainting, enabling targeted audio editing and the continuation of short recordings. Our latent diffusion models operate on top of a novel semantic-acoustic autoencoder that projects audio into a compact latent space, enabling efficient diffusion-based generation while preserving audio fidelity and encouraging semantic structure in the latent. Finally, we run adversarial post-training to both accelerate inference and improve generation quality, reducing the number of inference steps while improving fidelity and prompt adherence. Stable Audio 3 models are trained on licensed and Creative Commons data to generate music and sounds in less than a 2s on an H200 GPU and less than a few seconds on a MacBook Pro M4. We release the weights of small and medium, that can run on consumer-grade hardware, together with their training and inference pipeline.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Sound effects generation | Sound Effects (test) | FAD0.259 | 22 | |
| Sound effects generation | BBC Sound Effects Dataset | FAD0.358 | 8 | |
| Instrumental Music Generation | SDD 120s generations (test) | FAD0.101 | 6 | |
| Instrumental Music Generation | SDD 190s generations | FAD0.1 | 5 |