Meta Muse Image Text To Image API Documentation

Meta Muse Image Text To Image API Documentation

Playground

Try it on WaveSpeedAI!

Meta Muse Image Text-to-Image generates high-quality images from text prompts for creative visuals, concept art, marketing assets, social content, and production workflows. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Meta Muse Image Text-to-Image generates high-quality images from text prompts. Describe the subject, composition, lighting, style, and visual details, then choose an aspect ratio and output format to create the final image.


Why Choose This?

  • Text-to-image generation
    Generate images directly from natural-language prompts.

  • Simple creative workflow
    Provide a prompt, select layout settings, and generate an image in one request.

  • Flexible aspect ratio
    Choose the output aspect ratio based on your target format.

  • Multiple output formats
    Select the image format that fits your workflow.

  • Low-cost image generation
    Generate images at a fixed price per image.


Parameters

ParameterRequiredDescription
promptYesText prompt describing the image to generate. Include subject, scene, composition, lighting, mood, and style.
aspect_ratioNoAspect ratio of the generated image. Default: 1:1.
output_formatNoOutput image format. For example: webp.

How to Use

  1. Write your prompt — Describe the subject, environment, style, lighting, and composition.
  2. Choose aspect ratio — Select the layout that matches your target format.
  3. Choose output format — Select the image format for the generated output.
  4. Submit — Generate the final image and retrieve the output URL.

Pricing

Pricing is fixed at $0.011 per image.

OutputCost
One generated image$0.011

Best Use Cases

  • Creative image generation — Create original images from text prompts.
  • Concept art — Explore characters, scenes, objects, and visual styles.
  • Marketing visuals — Generate images for campaigns, ads, and social media.
  • Product concepts — Create visual ideas for product presentation and creative testing.
  • Fast prompt iteration — Test different visual directions at low cost.

Pro Tips

  • Use clear prompts with subject, composition, lighting, style, and background details.
  • Choose 1:1 for square images and other aspect ratios for platform-specific layouts.
  • Keep the prompt focused on one main scene or subject for better results.
  • Add camera, lighting, and mood details when you need a more polished visual style.
  • Use webp when you want compact web-friendly image output.

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",
  "aspect_ratio": "1:1",
  "output_format": "webp"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/meta/muse-image/text-to-image" \
  -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 "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id
' >&2
  exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"

# 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|deleted) printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done

Parameters

Task Submission Parameters

Request Parameters

ParameterTypeRequiredDefaultRangeDescription
promptstringYes-Describe the image to generate or the edit to apply.
aspect_ratiostringNo1:121:9, 16:9, 4:3, 3:2, 1:1, 2:3, 3:4, 9:16, 9:21-
output_formatstringNowebpwebp, png, jpeg-

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.statusstringTask status. completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses.
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.statusstringStatus: completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses
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
© 2026 WaveSpeedAI. All rights reserved.