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Mureka Ai Stem Song

Mureka Ai Stem Song

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Mureka AI Stem Song is a fast AI music model that creates stem song outputs via the official Mureka API. Ready-to-use REST inference API for AI music generation, vocal and instrumental stem workflows, remixing, music production, creative audio projects, and professional song creation with simple integration, no coldstarts, and affordable pricing.

Features

Mureka AI Stem Song

Mureka AI Stem Song is a fast AI music model for stem-based audio workflows. Upload a song or audio track, choose a separation model, and generate stem outputs for remixing, vocal/instrumental workflows, editing, and music production tasks.


Why Choose This?

  • Fast stem generation Separate an input track into usable stem outputs for remixing, editing, and production workflows.

  • Multiple separation models Choose between available stem models such as audio-separation-1 and audio-separation-2.

  • Simple audio workflow Upload one audio file, choose a model, and generate the separated output with minimal setup.

  • Useful for production and editing Suitable for vocal isolation, instrumental extraction, remix preparation, and creative audio workflows.

  • Production-ready API Easy to integrate into music tooling, audio apps, and content-production pipelines.


Parameters

ParameterRequiredDescription
audioYesInput audio track to process.
modelNoStem separation model to use, such as audio-separation-1 or audio-separation-2.

How to Use

  1. Upload your audio — provide the source song or audio file you want to process.
  2. Choose the model — select the separation model that best fits your workflow.
  3. Submit — run the model and download the generated stem output.

Example Use Case

Upload a full song to separate vocals and instrumental layers for remixing, re-editing, or production cleanup.


Pricing

Just $0.06 per song.


Best Use Cases

  • Stem separation — Extract parts of a track for editing and reuse.
  • Music production — Prepare vocals or instrumentals for remixing and arrangement work.
  • Content creation — Generate cleaner audio components for videos, shorts, and social content.
  • Remix workflows — Isolate audio elements for mashups, reinterpretations, and creative edits.
  • Audio cleanup and reuse — Separate usable parts of an existing recording for downstream production.

Pro Tips

  • Use the cleanest source audio available for better stem quality.
  • Try both available models if you want to compare separation behavior.
  • Full mixes with clear vocals and instrumentation often produce more usable stems.
  • Review the separated outputs before using them in final production workflows.

Notes

  • audio is required.
  • model is optional.
  • Pricing is fixed at $0.06 per song.

  • Other Mureka AI music generation and audio processing models may be useful when you need different music or audio workflows.

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/stem-song" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "model": "audio-separation-2"
}'

# 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
audiostringYes--Audio URL to separate into stems. Mureka accepts mp3/m4a URLs; this field is mapped to url.
modelstringNoaudio-separation-2audio-separation-1, audio-separation-2Mureka stem separation model. audio-separation-2 supports MIDI export.

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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