Mirelo SFX1.6 Video to Audio is a fast AI audio generation model that creates synchronized sound effects for video and returns the video with a new audio track. Supports clips up to 60 seconds. Ready-to-use REST inference API for video sound design, synced SFX generation, game trailers, social media clips, cinematic videos, product demos, and professional audio-for-video workflows with simple integration, no coldstarts, and affordable pricing.
Idle

$0.01per run·~100 / $1
Mirelo AI SFX 1.6 Video-to-Video generates synchronized sound effects for an uploaded video, with optional prompt guidance, multiple variations, and seed control for reproducibility. It is designed for adding or redesigning audio for short videos, trailers, demos, gameplay clips, and other visual content workflows.
Video-to-sound workflow Generate synchronized sound effects directly from video input.
Prompt-guided audio generation Add an optional text prompt to steer the type, mood, or intensity of the generated sound effects.
Multiple variations
Generate up to 4 variations in one request with num_samples.
Flexible audio duration
Choose how many seconds of SFX audio to generate, up to 60 seconds.
Seed support
Use seed for more reproducible results, or -1 for random generation.
Production-ready API Useful for sound design, trailer audio, short-form video, social content, and creative audio workflows.
| Parameter | Required | Description |
|---|---|---|
| video | Yes | Video URL or uploaded video to add synchronized sound effects to. |
| prompt | No | Optional text prompt to guide the generated sound effects. |
| duration | No | Duration of the generated SFX audio in seconds. Range: 1–60. Default: 10. This does not extend the input video. |
| num_samples | No | Number of variations to generate. Range: 1–4. Default: 1. |
| seed | No | Seed for reproducibility. Use -1 for a random seed. Default: -1. |
1 to 4.-1 for random output, or a fixed value for more reproducible results.Cinematic trailer sound design with deep impacts, airy risers, subtle whooshes, and tense low-end atmosphere
Pricing is based on generated SFX duration and number of samples.
| Duration | 1 Sample | 2 Samples | 3 Samples | 4 Samples |
|---|---|---|---|---|
| 1s | $0.01 | $0.02 | $0.03 | $0.04 |
| 5s | $0.05 | $0.10 | $0.15 | $0.20 |
| 10s | $0.10 | $0.20 | $0.30 | $0.40 |
| 20s | $0.20 | $0.40 | $0.60 | $0.80 |
| 30s | $0.30 | $0.60 | $0.90 | $1.20 |
| 60s | $0.60 | $1.20 | $1.80 | $2.40 |
duration and num_samplesprompt and seed do not affect pricingduration does not extend the input videonum_samples when you want multiple design options from the same clip.seed when comparing prompt changes on the same source video.video is required.duration supports 1–60 seconds.num_samples supports 1–4.seed = -1 means random generation.duration refers to the SFX audio length only and does not extend the uploaded video.Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/mirelo-ai/sfx-1.6/video-to-video with your input as JSON. The endpoint returns a prediction id. Start polling the result endpoint around every 2 seconds, increase the interval for long-running tasks, and stop on any terminal status. On completed, read output values from data.outputs. Examples for Sfx 1.6 Video To Video below.
set -euo pipefail
: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"
REQUEST_BODY=$(cat <<'JSON'
{
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"duration": 10,
"num_samples": 1,
"seed": -1
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/mirelo-ai/sfx-1.6/video-to-video" \
-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/mirelo-ai/sfx-1.6/video-to-video";
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 ${apiKey}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"duration": 10,
"num_samples": 1,
"seed": -1
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
`https://api.wavespeed.ai/api/v3/predictions/${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 = {
"video": "https://interactive-examples.mdn.mozilla.net/media/cc0-videos/flower.mp4",
"duration": 10,
"num_samples": 1,
"seed": -1
}
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/mirelo-ai/sfx-1.6/video-to-video", 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)Sfx 1.6 Video To Video is a Mirelo Ai model for AI inference, exposed as a REST API on WaveSpeedAI. Mirelo SFX1.6 Video to Audio is a fast AI audio generation model that creates synchronized sound effects for video and returns the video with a new audio track. Supports clips up to 60 seconds. Ready-to-use REST inference API for video sound design, synced SFX generation, game trailers, social media clips, cinematic videos, product demos, and professional audio-for-video 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/mirelo-ai/mirelo-ai-sfx-1.6-video-to-video.
Sfx 1.6 Video To Video starts at $0.010 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`, `video`, `duration`, `seed`, `num_samples`. 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/mirelo-ai/mirelo-ai-sfx-1.6-video-to-video.
Median end-to-end generation time on WaveSpeedAI is around 29 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (Mirelo Ai). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.