Stability Ai Stable Audio 3 Audio Inpainting

Stability Ai Stable Audio 3 Audio Inpainting

Playground

Stable Audio 3 Audio Inpainting is a fast AI audio editing model that regenerates a selected region of an audio clip from a prompt while preserving the surrounding audio. Ready-to-use REST inference API for audio repair, sound effect editing, segment regeneration, music production, game audio, video sound design, and professional audio inpainting workflows with simple integration, no coldstarts, and affordable pricing.

Features

Stability AI Stable Audio 3 Audio-Inpainting

Stability AI Stable Audio 3 Audio-Inpainting replaces a selected region inside an existing audio clip using a natural-language prompt. It is designed for localized audio editing workflows where you want to rewrite only part of a clip while preserving the rest of the original audio.

Why Choose This?

• Region-based audio replacement
  Replace only the selected section of an audio clip instead of regenerating the whole file.

• Prompt-guided inpainting
  Use a text prompt to describe what the new audio inside the masked region should sound like.

• Negative prompt support
  Add negative_prompt to reduce unwanted sounds or qualities in the generated result.

• Preserves surrounding audio
  Audio outside the selected inpaint range remains unchanged.

• Flexible output formats
  Export results in mp3, wav, flac, ogg, opus, m4a, or aac.

• Production-ready API
  Suitable for sound repair, replacement, transition cleanup, ambient editing, and creative post-production workflows.

Parameters

How to Use

1. Upload your source audio — provide the clip you want to edit.
2. Write your prompt — describe what the replacement audio inside the selected region should sound like.
3. Set the inpaint range — choose mask_start_seconds and mask_end_seconds to define the region to replace.
4. Add a negative prompt (optional) — list sounds or qualities you want to avoid.
5. Adjust generation controls (optional) — tune num_inference_steps and guidance_scale if needed.
6. Choose output format — select the format that best fits your workflow.
7. Submit — run the model and download the edited audio.

Example Prompt

Replace this section with a softer cinematic ambience, distant wind, subtle metallic resonance, and a smoother transition into the following audio.

Pricing

Just $0.0442 per request.

Billing Rules

• Each inpainting request costs $0.0442
• Pricing is fixed per request
• mask_start_seconds, mask_end_seconds, negative_prompt, num_inference_steps, guidance_scale, and output_format do not affect pricing

Best Use Cases

• Audio repair — Replace damaged or unwanted segments inside an existing clip.
• Transition cleanup — Smooth over awkward cuts or rough edits in a timeline.
• Sound redesign — Change one localized part of a scene without affecting the rest.
• Creative post-production — Rewrite small sections of a soundtrack or ambience bed.
• Effect replacement — Swap out a specific sound event while keeping surrounding context intact.

Pro Tips

• Keep the masked region as tight as possible for more controlled replacement.
• Use prompts that match the tone and texture of the surrounding audio for smoother blending.
• Add a negative_prompt when you want to avoid music, vocals, distortion, or unwanted effects.
• Increase num_inference_steps if you want potentially more refined results and can tolerate more runtime.
• Choose wav or flac when you plan further editing after generation.

Notes

• audio and prompt are required.
• mask_start_seconds and mask_end_seconds define the exact region to replace.
• mask_end_seconds must be greater than mask_start_seconds.
• Audio outside the selected mask range is preserved.
• Pricing is fixed at $0.0442 per request.

Related Models

• Stability AI Stable Audio 3 Text-to-Audio — Generate audio directly from a text prompt.
• Stability AI Stable Audio 3 Audio-Outpainting — Extend an existing audio clip before and/or after the source.
• Other audio editing workflows — Useful when you need continuation, regeneration, or more specialized sound design controls.

<ApiPage model={model}>
  ## Authentication

  For authentication details, please refer to the [Authentication Guide](/docs-authentication).

  ## API Endpoints

  ### Submit Task & Query Result

  ## Parameters

  ### Task Submission Parameters

  #### Request Parameters

  #### Response Parameters

  <SubmitResponse />

  #### Result Request Parameters

  | Parameter | Type | Required | Default | Description |
  |-----------|------|----------|---------|-------------|
  | id | string | Yes | - | Task ID |

  #### Result Response Parameters

  | Parameter | Type | Description |
  |-----------|------|-------------|
  | code | integer | HTTP status code (e.g., 200 for success) |
  | message | string | Status message (e.g., "success") |
  | data | object | The prediction data object containing all details |
  | data.id | string | Unique identifier for the prediction, the ID of the prediction to get |
  | data.model | string | Model ID used for the prediction |
  | data.outputs | string | Array of generated audio URLs. |
  | data.urls | object | Object containing related API endpoints |
  | data.urls.get | string | URL to retrieve the prediction result |
  | data.status | string | Status of the task: `created`, `processing`, `completed`, or `failed` |
  | data.created_at | string | ISO timestamp of when the request was created (e.g., "2023-04-01T12:34:56.789Z") |
  | data.error | string | Error message (empty if no error occurred) |
  | data.timings | object | Object containing timing details |
  | data.timings.inference | integer | Inference time in milliseconds |

</ApiPage>