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Mureka AI V7.6 Generate BGM is a fast AI music generation model that creates high-quality background music via the official Mureka API. Ready-to-use REST inference API for AI BGM generation, video soundtracks, game music, podcast intros, advertising audio, social media content, and professional music production workflows with simple integration, no coldstarts, and affordable pricing.

text-to-audio
इनपुट

निष्क्रिय

$0.03प्रति रन·~33 / $1

उदाहरणसभी देखें

Dreamy female vocal pop song with soft electronic beat, emotional piano chords, atmospheric pads, catchy hook, romantic cinematic mood, modern pop production, clean mix, suitable for short video background music

संबंधित मॉडल

README

Mureka AI V7.6 Generate BGM

Mureka AI V7.6 Generate BGM creates background music tracks from a text prompt, with optional instrumental reference guidance and support for multiple generations in a single request. It is suitable for videos, podcasts, ads, games, livestreams, and other content workflows that need original non-vocal music.

Why Choose This?

  • Prompt-based background music generation Generate instrumental tracks from a natural-language description of mood, genre, tempo, or instrumentation.

  • Optional instrumental reference guidance Use instrumental_id to guide the generation toward a particular musical direction.

  • Multiple generations per run Generate up to 3 background music tracks in one request with number_of_songs.

  • Flexible output formats Export generated tracks as mp3, wav, or flac.

  • Simple pricing Pricing depends only on how many tracks you generate.

Parameters

ParameterRequiredDescription
promptYesPrompt describing the background music. Official limit: up to 1024 characters.
number_of_songsNoNumber of generations. Range: 1–3. Default: 1.
output_formatNoOutput audio format after re-uploading to WaveSpeed CDN. Supported values: mp3, wav, flac. Default: mp3.
instrumental_idNoOptional Mureka uploaded instrumental reference file ID.

How to Use

  1. Write your prompt — describe the mood, genre, tempo, instrumentation, and production style you want.
  2. Add an instrumental reference (optional) — provide instrumental_id if you want stronger musical guidance.
  3. Set number of songs — choose how many generations you want, from 1 to 3.
  4. Choose output format — select mp3, wav, or flac.
  5. Submit — run the model and download the generated background music tracks.

Example Prompt

Dreamy female vocal pop song with soft electronic beat, emotional piano chords, atmospheric pads, catchy hook, romantic cinematic mood, modern pop production, clean mix, suitable for short video background music

Pricing

Pricing is based on number_of_songs.

Number of SongsCost
1$0.03
2$0.06
3$0.09

Billing Rules

  • Each generated background music track costs $0.03
  • Total price = $0.03 × number_of_songs
  • output_format and instrumental_id do not affect pricing

Best Use Cases

  • Video background music — Generate instrumental tracks for vlogs, ads, explainers, and short-form content.
  • Podcast and livestream music — Create intro, outro, or ambient background tracks.
  • Game and app audio — Produce mood-based background music for interactive experiences.
  • Creative ideation — Explore multiple music directions from a single prompt.
  • Reference-guided generation — Use an instrumental reference to steer the musical style more precisely.

Pro Tips

  • Be specific in your prompt about genre, tempo, instrumentation, and mood.
  • Use number_of_songs when you want multiple variations from the same idea.
  • Add instrumental_id only when you need tighter musical guidance.
  • Start with mp3 for convenience, then use wav or flac when higher-quality output matters more.
  • Short, focused prompts often produce more controllable results than overly broad descriptions.

Notes

  • prompt is required.
  • number_of_songs supports values from 1 to 3.
  • prompt supports up to 1024 characters.
  • output_format defaults to mp3.
  • Pricing depends only on number_of_songs.

Related Models

नोट:यह वेबसाइट तृतीय पक्षों द्वारा प्रदान किए गए AI मॉडलों का उपयोग करती है। दस्तावेज़ की कीमतें केवल संदर्भ के लिए हैं और पुरानी हो सकती हैं। Generate बटन अनुमान दिखाता है; टास्क का अंतिम शुल्क ही मान्य होगा।

Mureka v7.6 Generate Bgm API — Quick start

Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/mureka-ai/mureka-v7.6/generate-bgm 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 Mureka v7.6 Generate Bgm below.

HTTP example
set -euo pipefail

: "${WAVESPEED_API_KEY:?Set WAVESPEED_API_KEY}"

REQUEST_BODY=$(cat <<'JSON'
{
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "number_of_songs": 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/mureka-ai/mureka-v7.6/generate-bgm" \
  -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
done
Node.js example
const submitUrl = "https://api.wavespeed.ai/api/v3/mureka-ai/mureka-v7.6/generate-bgm";
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 ${apiKey}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
        "prompt": "A cinematic shot of a city at sunset, soft golden light",
        "number_of_songs": 1,
        "output_format": "mp3"
}),
});
const task = body.data ?? body;
if (!task.id) throw new Error("Submission response did not contain a prediction id");
const resultUrl = task.urls?.get ||
  `https://api.wavespeed.ai/api/v3/predictions/${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));
}
Python example
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 = {
    "prompt": "A cinematic shot of a city at sunset, soft golden light",
    "number_of_songs": 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/mureka-ai/mureka-v7.6/generate-bgm", 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)

Mureka v7.6 Generate Bgm API — Frequently asked questions

What is the Mureka v7.6 Generate Bgm API?

Mureka v7.6 Generate Bgm is a Mureka Ai model for audio generation, exposed as a REST API on WaveSpeedAI. Mureka AI V7.6 Generate BGM is a fast AI music generation model that creates high-quality background music via the official Mureka API. Ready-to-use REST inference API for AI BGM generation, video soundtracks, game music, podcast intros, advertising audio, social media content, and professional music production workflows with simple integration, no coldstarts, and affordable pricing. You can call it programmatically or try it from the playground above.

How do I call the Mureka v7.6 Generate Bgm API?

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/mureka-ai/mureka-ai-mureka-v7.6-generate-bgm.

How much does Mureka v7.6 Generate Bgm cost per run?

Mureka v7.6 Generate Bgm starts at $0.030 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.

What inputs does Mureka v7.6 Generate Bgm accept?

Key inputs: `prompt`, `instrumental_id`, `number_of_songs`, `output_format`. 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/mureka-ai/mureka-ai-mureka-v7.6-generate-bgm.

How long does Mureka v7.6 Generate Bgm take to generate?

Median end-to-end generation time on WaveSpeedAI is around 51 seconds per request, based on recent successful runs. Queue time varies with global demand; live status is visible in the prediction record.

Can I use Mureka v7.6 Generate Bgm outputs commercially?

Commercial usage rights depend on the model's license, set by its provider (Mureka Ai). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.

Mureka V7.6 Generate Bgm | AI Music Generation API on WaveSpeedAI