Google Lyria 3 Pro Music

Google Lyria 3 Pro Music

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Google Lyria 3 Pro generates high-quality music tracks from text prompts and optional image input. Pro tier delivers enhanced audio quality and richer compositions. Produces complete songs with lyrics, descriptions, and audio output. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Google Lyria 3 Pro is Google’s premium AI music generation model. Describe the sound you want in natural language — genre, tempo, instruments, mood, and style — and get a higher-fidelity music clip with richer detail and more nuanced musical expression than the standard Clip tier. Optionally guide the output with a reference image or refine it with a negative prompt.


Why Choose This?

  • Premium music generation quality Richer instrumentation, more nuanced musical expression, and higher audio fidelity than the Clip tier.

  • Detailed text-to-music control Describe your track with genre, BPM, instruments, energy level, and mood for precise, on-target results.

  • Image-guided generation Upload a reference image to inspire the musical mood and atmosphere of the clip.

  • Negative prompt support Specify what you don’t want in the track — exclude instruments, styles, or characteristics for more precise control.

  • Reproducible results Use the seed parameter to lock in a specific output for exact reproduction across runs.

  • Prompt Enhancer Built-in tool to automatically refine your music descriptions for richer results.


Parameters

ParameterRequiredDescription
promptYesText description of the desired music style, genre, tempo, and instruments.
imageNoReference image to guide the mood and atmosphere of the generated music.
negative_promptNoElements to exclude from the generated track.
seedNoRandom seed for reproducible results.

How to Use

  1. Write your prompt — describe the genre, tempo, instruments, mood, and style. Use the Prompt Enhancer for better results.
  2. Upload a reference image (optional) — provide an image to inspire the musical atmosphere.
  3. Add a negative prompt (optional) — specify sounds, styles, or elements you want to avoid.
  4. Set a seed (optional) — fix the seed to reproduce a specific result in future runs.
  5. Submit — generate and download your music clip.

Example Prompt

Dark ambient sci-fi underscore, deep pulsing bass drones, ethereal synth pads, subtle percussion, tense and mysterious, space horror atmosphere, no melody, slow tempo.


Pricing

Just $0.08 per clip.


Best Use Cases

  • Film & Video Scoring — Generate high-quality music beds and underscore for professional video productions.
  • Game & Interactive Media — Produce rich atmospheric tracks and dynamic soundscapes for games and apps.
  • Advertising & Brand Content — Create polished custom music for campaigns without licensing fees.
  • Podcast & Streaming — Generate premium intro, outro, and background music for audio content.
  • Creative Production — Rapidly prototype and explore musical styles with professional-grade output.

Pro Tips

  • Be specific about BPM, key instruments, and energy level for the most accurate results.
  • Use negative_prompt to exclude unwanted elements like vocals, specific instruments, or genres.
  • Fix the seed once you find a style you like to iterate on it consistently.
  • Try pairing atmospheric images with a minimal prompt to let the image drive the mood.
  • Use the Prompt Enhancer to expand a simple style reference into a detailed music description.

Notes

  • Only prompt is required; all other parameters are optional.
  • Please ensure your content complies with Google’s usage policies.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result

set -euo pipefail

export WAVESPEED_API_KEY="your-api-key"

REQUEST_BODY=$(cat <<'JSON'
{
  "prompt": "A cinematic ocean wave at sunrise, highly detailed"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/google/lyria-3-pro/music" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}")

TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL=$(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' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  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

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
promptstringYes-The positive prompt for the generation.
imagestringNo-The image for generating the output.
negative_promptstringNo-A description of what to exclude from the generated audio.
seedintegerNo--The random seed to use for the generation. -1 means a random seed will be used.

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.outputsarrayOutput values, usually URL strings; some models return text strings or structured result objects (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
data.modelstringModel ID used for the prediction
data.outputsarray<string | object>Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model.
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to poll for the prediction result
data.statusstringStatus: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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