Stable Audio 3.0 Medium
Stable Audio 3.0 Medium provides downloadable weights for music and general sound generation. It uses latent diffusion with a semantic-acoustic autoencoder, and supports targeted edits and continuation of existing audio.
Model design and access
Adversarial post-training reduces the number of sampling steps. The card's example uses eight steps. Text conditioning uses T5Gemma, while the diffusion model operates on compressed audio. The downloadable package should be assessed as a full pipeline, including the text encoder and decoder.Stable Audio 3.0 Medium official model documentation
The separate Medium Base checkpoint is the pretrained starting point for adaptation. The post-trained Medium checkpoint is the direct generation release. Optimized variants belong to this same model family.Stable Audio 3: official inference repository
Practical use
Practical guidance. Medium is a practical choice when a team needs to keep inference and adaptation within its own environment. Measure memory with the intended track length and decoder settings. Short preview clips can help assess a prompt before requesting a full track; a small text change can still change the composition.
Specifications & access
| Detail | Value and conditions |
|---|---|
| Access | Downloadable |
| Model identifiers | stable-audio-3-mediumstable-audio-3-medium-base |
| Model size | 1.4 billion parameters in the official model table.Stable Audio 3: official inference repository |
| Maximum sequence | 380 seconds; GPU-oriented inference.Stable Audio 3: official inference repository |
| License | Stability AI Community License; T5Gemma has separate Gemma terms.Stable Audio 3.0 Medium official model documentation |
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