Browse ModelsMureka AIMureka AI Mureka V7.6 Generate Song

Mureka Ai Mureka V7.6 Generate Song

Mureka Ai Mureka V7.6 Generate Song

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Mureka AI V7.6 Generate Song is a fast AI music generation model that creates high-quality songs via the official Mureka API. Ready-to-use REST inference API for AI song generation, lyrics-to-music workflows, vocal music creation, demo production, creative audio projects, and professional music generation with simple integration, no coldstarts, and affordable pricing.

Features

Mureka AI V7.6 Recognize Song

Mureka AI V7.6 Recognize Song is a music recognition model for analyzing uploaded audio and identifying song-related information from the input track. It is suitable for song recognition, music metadata workflows, catalog matching, and other audio analysis tasks.


Why Choose This?

  • Song recognition workflow Analyze an uploaded audio track and return recognized song information.

  • Simple audio input Upload a single audio file and run recognition without additional configuration.

  • Useful for metadata workflows Suitable for music identification, catalog management, and audio analysis pipelines.

  • Fast API integration Easy to integrate into music tools, media workflows, and content analysis systems.

  • Fixed pricing Uses a simple flat price per recognition request.


Parameters

ParameterRequiredDescription
audioYesInput audio track to analyze and recognize.

How to Use

  1. Upload your audio — provide the song or music clip you want to analyze.
  2. Submit — run the recognition request.
  3. Review the result — use the returned song recognition output in your workflow.

Example Use Case

Upload a music clip to identify the song and support catalog lookup or metadata verification workflows.


Pricing

Just $0.03 per request.


Best Use Cases

  • Song identification — Recognize songs from uploaded audio clips.
  • Music catalog workflows — Match tracks against library or metadata systems.
  • Audio analysis pipelines — Use recognition as part of larger music-processing workflows.
  • Content management — Verify or enrich music-related metadata.
  • Media operations — Support ingestion, tagging, and review processes for music assets.

Pro Tips

  • Upload clear audio for better recognition results.
  • Use the cleanest source clip available when possible.
  • Tracks with clear vocals and strong musical detail are generally easier to recognize.
  • Avoid heavily distorted, noisy, or low-quality uploads when accuracy matters.

Notes

  • audio is required.
  • Pricing is fixed at $0.03 per request.
  • If the uploaded song has unclear or indistinct lyrics, the model may be unable to extract lyric-related information accurately.
  • Very noisy, low-quality, or heavily mixed audio may reduce recognition quality.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result


# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/mureka-ai/mureka-v7.6/generate-song" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "number_of_songs": 1,
    "output_format": "mp3"
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
lyricsstringYes--Lyrics for the generated song. Official limit: up to 3000 characters.
promptstringNo-Optional style prompt for the song. Official limit: up to 1024 characters.
number_of_songsintegerNo11 ~ 3Number of generations. Mureka charges per generated item.
output_formatstringNomp3mp3, wav, flacOutput audio format after re-uploading to WaveSpeed CDN.
reference_idstringNo--Optional Mureka uploaded reference file ID.
vocal_idstringNo--Optional Mureka uploaded vocal file ID.
melody_idstringNo--Optional Mureka uploaded melody file ID.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayArray of URLs to the generated content (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction, the ID of the prediction to get
data.modelstringModel ID used for the prediction
data.outputsstringArray of URLs to the generated content.
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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