Prefect Pony Xl

Prefect Pony Xl

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Prefect Pony XL delivers high-quality anime-style image generation for character art and illustrations. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Generate stunning, highly stylized images with Prefect Pony XL — a powerful text-to-image model optimized for vibrant, artistic outputs. With customizable dimensions and fast generation, it’s perfect for creative projects that demand expressive, eye-catching visuals.

Why It Looks Great

  • Artistic excellence: Optimized for vibrant colors, high contrast, and expressive artistic styles.
  • Custom dimensions: Flexible width and height controls for any aspect ratio or resolution.
  • Prompt Enhancer: Built-in tool to automatically refine and expand your descriptions.
  • Multiple output formats: Export as JPEG or PNG based on your needs.
  • Reproducible results: Use the seed parameter to recreate exact outputs or explore variations.
  • Budget-friendly: High-quality artistic generation at an accessible price point.

Parameters

ParameterRequiredDescription
promptYesText description of the image you want to generate.
sizeNoCustom dimensions with separate width and height controls.
widthNoOutput width in pixels (e.g., 1024).
heightNoOutput height in pixels (e.g., 1024).
seedNoRandom seed for reproducibility. Use -1 for random.
output_formatNoOutput file format: jpeg webp or png. Default: jpeg.

How to Use

  1. Write your prompt — describe your image with details about subject, style, colors, and mood.
  2. Use Prompt Enhancer (optional) — click to automatically enrich your description.
  3. Set dimensions — adjust width and height sliders to your desired resolution.
  4. Set seed (optional) — use -1 for random, or a specific number to reproduce results.
  5. Choose output format — select jpeg for smaller files or png for transparency support.
  6. Run — click the button to generate.
  7. Download — preview and save your image.

Pricing

Flat rate per image generation.

OutputCost
Per image$0.015

Best Use Cases

  • Artistic Portraits — Create vibrant, stylized character portraits with bold aesthetics.
  • Illustration & Concept Art — Generate expressive artwork for creative projects.
  • Social Media Content — Produce eye-catching visuals that stand out in feeds.
  • Album & Poster Art — Design striking cover art and promotional graphics.
  • Creative Exploration — Experiment with artistic styles affordably at high volume.

Example Prompts

  • “A portrait of a young artist with colorful paint splashes across their face, wearing eccentric bohemian clothing, surrounded by abstract graffiti, vibrant tones, high-contrast artistic photo”
  • “Mystical forest spirit with glowing antlers, ethereal mist, bioluminescent flora, fantasy art style”
  • “Retro-futuristic cityscape at dusk, flying cars, neon advertisements, synthwave color palette”
  • “Elegant koi fish swimming through cherry blossom petals, traditional Japanese art meets modern digital painting”
  • “Steampunk inventor in her workshop, brass gears, warm candlelight, detailed Victorian aesthetic”

Pro Tips for Best Results

  • Emphasize artistic style keywords — “vibrant”, “high-contrast”, “stylized”, “artistic” enhance the model’s strengths.
  • Describe color palettes explicitly for more controlled outputs.
  • Use the Prompt Enhancer to add artistic details you might not have considered.
  • For portraits, include details about expression, lighting, and background atmosphere.
  • Square dimensions (1024x1024) work well for balanced compositions; adjust for specific formats.
  • Use PNG format when you need higher quality or potential transparency.

Notes

  • Generation time may vary based on resolution and current queue load.
  • Higher resolutions may take slightly longer to process.
  • The model excels at artistic and stylized imagery — lean into creative, expressive prompts.

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",
  "size": "1024*1024",
  "seed": -1,
  "output_format": "jpeg"
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/prefect-pony-xl" \
  -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.
sizestringNo1024*1024-The size of the generated media in pixels (width*height).
seedintegerNo-1-The random seed to use for the generation. -1 means a random seed will be used.
output_formatstringNojpegjpeg, png, webpThe format of the output image.
enable_base64_outputbooleanNofalse-If set to `true`, the prediction's `output` strings are returned as **naked base64** (no `data:<mime>;base64,` prefix). When `false` (default), outputs are returned as URLs pointing to our CDN.
enable_sync_modebooleanNofalse-If set to `true`, the request attempts to wait for the generated result and return outputs in the same response. If the result is not ready within the sync wait window, the API can return a timeout body while the task continues processing. This option is only available via the API and is supported only by some models.

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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