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.
Idle
$0.0442per run·~22 / $1
blue-hour synthwave drive
Velvet Room future R&B bounce.
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.
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.
| Parameter | Required | Description |
|---|---|---|
| audio | Yes | Source audio to edit. |
| prompt | Yes | Text prompt describing the replacement audio for the masked region. |
| mask_start_seconds | No | Start time of the region to inpaint, in seconds. Default: 0. |
| mask_end_seconds | No | End time of the region to inpaint, in seconds. Must be greater than mask_start_seconds. Default: 5. |
| negative_prompt | No | Optional terms to avoid in the generated audio. |
| num_inference_steps | No | Number of inference steps. Range: 1–100. Default: 8. |
| guidance_scale | No | Prompt guidance strength. Range: 0–25. Default: 1. |
| output_format | No | Output audio format. Supported values: mp3, wav, flac, ogg, opus, m4a, aac. Default: mp3. |
mask_start_seconds and mask_end_seconds to define the region to replace.num_inference_steps and guidance_scale if needed.Replace this section with a softer cinematic ambience, distant wind, subtle metallic resonance, and a smoother transition into the following audio.
Just $0.0442 per request.
mask_start_seconds, mask_end_seconds, negative_prompt, num_inference_steps, guidance_scale, and output_format do not affect pricingnegative_prompt when you want to avoid music, vocals, distortion, or unwanted effects.num_inference_steps if you want potentially more refined results and can tolerate more runtime.wav or flac when you plan further editing after generation.audio and prompt are required.mask_start_seconds and mask_end_seconds define the exact region to replace.mask_end_seconds must be greater than mask_start_seconds.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/stability-ai/stable-audio-3/audio-inpainting with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Stable Audio 3 Audio Inpainting below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"mask_start_seconds": 0,
"mask_end_seconds": 5,
"num_inference_steps": 8,
"guidance_scale": 1,
"output_format": "mp3"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/stability-ai/stable-audio-3/audio-inpainting" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d "$REQUEST_BODY")
TASK=$(printf '%s' "$SUBMIT_RESPONSE" | jq 'if has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "$TASK" | jq -r '.id')
if [ -z "$PREDICTION_ID" ] || [ "$PREDICTION_ID" = "null" ]; then
printf 'Submission response did not contain a prediction id
' >&2
exit 1
fi
RESULT_URL=$(printf '%s' "$TASK" | jq -r '.urls.get // empty')
if [ -z "$RESULT_URL" ]; then
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/$PREDICTION_ID/result"
fi
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(curl --silent --show-error --fail-with-body "$RESULT_URL" \
-H "Authorization: Bearer $WAVESPEED_API_KEY")
RESULT=$(printf '%s' "$RESPONSE" | jq 'if has("data") then .data else . end')
STATUS=$(printf '%s' "$RESULT" | jq -r '.status')
case "$STATUS" in
completed) printf '%s\n' "$RESULT" | jq '.outputs'; break ;;
failed|cancelled|timeout) printf '%s\n' "$RESULT" | jq . >&2; exit 1 ;;
created|processing) sleep 2 ;;
*) printf 'Unexpected status: %s
' "$STATUS" >&2; exit 1 ;;
esac
doneconst submitUrl = "https://api.wavespeed.ai/api/v3/stability-ai/stable-audio-3/audio-inpainting";
const apiKey = process.env.WAVESPEED_API_KEY;
if (!apiKey) throw new Error('Set WAVESPEED_API_KEY');
async function requestJson(url, options = {}) {
const response = await fetch(url, options);
if (!response.ok) throw new Error(await response.text());
return response.json();
}
// 1. Submit the prediction.
const body = await requestJson(submitUrl, {
method: "POST",
headers: {
"Authorization": `Bearer ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"mask_start_seconds": 0,
"mask_end_seconds": 5,
"num_inference_steps": 8,
"guidance_scale": 1,
"output_format": "mp3"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${task.id}/result`;
// 2. Poll until the prediction finishes.
while (true) {
const resultBody = await requestJson(resultUrl, {
headers: { "Authorization": `Bearer ${apiKey}` },
});
const result = resultBody.data ?? resultBody;
if (result.status === "completed") {
console.log(result.outputs);
break;
}
if (["failed", "cancelled", "timeout"].includes(result.status)) throw new Error(JSON.stringify(result));
if (!["created", "processing"].includes(result.status)) throw new Error("Unexpected status: " + result.status);
await new Promise(resolve => setTimeout(resolve, 2000));
}import json
import os
import time
from urllib.request import Request, urlopen
api_key = os.environ["WAVESPEED_API_KEY"]
headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
payload = {
"audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"mask_start_seconds": 0,
"mask_end_seconds": 5,
"negative_prompt": "",
"num_inference_steps": 8,
"guidance_scale": 1,
"output_format": "mp3"
}
def request_json(url, data=None):
request = Request(url, data=data, headers=headers, method="POST" if data else "GET")
with urlopen(request) as response:
return json.load(response)
# 1. Submit the prediction.
body = request_json("https://api.wavespeed.ai/api/v3/stability-ai/stable-audio-3/audio-inpainting", json.dumps(payload).encode())
task = body.get("data", body)
if not task.get("id"):
raise RuntimeError("Submission response did not contain a prediction id")
result_url = task.get("urls", {}).get("get") or f"https://api.wavespeed.ai/api/v3/predictions/{task['id']}/result"
# 2. Poll until the prediction finishes.
while True:
result_body = request_json(result_url)
result = result_body.get("data", result_body)
status = result.get("status")
if status == "completed":
print(result.get("outputs", []))
break
if status in {"failed", "cancelled", "timeout"}:
raise RuntimeError(result)
if status not in {"created", "processing"}:
raise RuntimeError(f"Unexpected status: {status}")
time.sleep(2)Stable Audio 3 Audio Inpainting is a Stability AI model for AI inference, exposed as a REST API on WaveSpeedAI. 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. You can call it programmatically or try it from the playground above.
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID. Poll the result endpoint starting around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. The playground generates production-oriented Python, JavaScript, and cURL examples with timeouts, transient-error handling, and safe GET retries. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/stability-ai/stability-ai-stable-audio-3-audio-inpainting.
Stable Audio 3 Audio Inpainting starts at $0.044 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
Key inputs: `prompt`, `audio`, `guidance_scale`, `num_inference_steps`, `negative_prompt`, `mask_end_seconds`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/stability-ai/stability-ai-stable-audio-3-audio-inpainting.
Sign up for a free WaveSpeedAI account to claim starter credits, copy your API key from /accesskey, then call the endpoint shown in the API tab of the playground. The playground also auto-generates a code sample in Python, JavaScript, or cURL for the parameters you've set.
Commercial usage rights depend on the model's license, set by its provider (Stability AI). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.