Stable Audio 3 Audio Outpainting is a fast AI audio extension model that extends a source audio clip before or after its existing content. Ready-to-use REST inference API for audio continuation, sound effect extension, ambient audio expansion, music production, game audio, video sound design, and professional audio editing workflows with simple integration, no coldstarts, and affordable pricing.
Idle
$0.0446per run·~22 / $1
Extend the source with a dark cinematic pulse, low cello drones, muted piano repetitions, subtle analog bass, and distant metallic textures; preserve the tempo and key, then build into a tense new phrase without vocals.
Stability AI Stable Audio 3 Audio-Outpainting extends an existing audio clip by generating new audio before and/or after the original source. It is designed for audio continuation, intro/outro expansion, ambient bed extension, scene transitions, and other prompt-guided audio editing workflows.
Audio extension in both directions
Add newly generated audio before the source clip, after it, or on both sides.
Prompt-guided outpainting
Use a text prompt to describe how the new extension audio should sound.
Negative prompt support
Add negative_prompt to reduce unwanted elements or steer away from specific sounds.
Flexible extension length
Independently control how many seconds to extend before and after the source audio.
Generation controls
Adjust num_inference_steps and guidance_scale for more control over output behavior.
Multiple export formats
Export results in mp3, wav, flac, ogg, opus, m4a, or aac.
| Parameter | Required | Description |
|---|---|---|
| audio | Yes | Source audio to extend. |
| prompt | Yes | Text prompt describing the extension audio. |
| extend_seconds_before | No | Seconds to extend before the original audio. Range: 0–380. Default: 0. |
| extend_seconds_after | No | Seconds to extend after the original audio. Range: 0–380. 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. |
num_inference_steps and guidance_scale if needed.Extend this ambient desert night recording with distant wind, subtle metallic creaks, low environmental rumble, and a natural cinematic continuation.
Just $0.0446 per request.
extend_seconds_before, extend_seconds_after, negative_prompt, num_inference_steps, guidance_scale, and output_format do not affect pricingnegative_prompt when you want to avoid music, vocals, distortion, or unwanted effects.num_inference_steps if you want potentially more refined results and can tolerate more runtime.wav or flac when you plan further editing.audio and prompt are required.extend_seconds_before and extend_seconds_after control how much new audio is generated around the original clip.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/stability-ai/stable-audio-3/audio-outpainting with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Stable Audio 3 Audio Outpainting below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"extend_seconds_before": 0,
"extend_seconds_after": 5,
"num_inference_steps": 8,
"guidance_scale": 1,
"output_format": "mp3"
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/stability-ai/stable-audio-3/audio-outpainting" \
-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-outpainting";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"extend_seconds_before": 0,
"extend_seconds_after": 5,
"num_inference_steps": 8,
"guidance_scale": 1,
"output_format": "mp3"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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",
"extend_seconds_before": 0,
"extend_seconds_after": 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-outpainting", 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 Outpainting is a Stability AI model for AI inference, exposed as a REST API on WaveSpeedAI. Stable Audio 3 Audio Outpainting is a fast AI audio extension model that extends a source audio clip before or after its existing content. Ready-to-use REST inference API for audio continuation, sound effect extension, ambient audio expansion, music production, game audio, video sound design, and professional audio editing 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-outpainting.
Stable Audio 3 Audio Outpainting starts at $0.045 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`, `extend_seconds_after`. 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-outpainting.
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.