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Stability Ai Sdxl

Stability Ai Sdxl

Playground

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Stability AI SDXL is a text-to-image generator that creates beautiful, high-quality images. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

SDXL — Text / Image-to-Image

SDXL is Stability AI’s flagship diffusion model for high-quality image generation. It excels at photorealism, stylized illustration, and product renders.

Key Features

  • Text-to-Image (T2I): Generate fully new images from natural-language prompts.
  • Image-to-Image (I2I): Transform an input image toward your prompt while preserving composition.

Modes & When to Use

  • T2I: Best for concepting and fresh compositions.
  • I2I: Use when you already like the framing/pose and want a new style or content consistent with the source.

Inputs & Parameters

  • prompt (required): Describe subject, style, lighting, camera, mood.
  • image: PNG/JPEG/WebP; used as the starting point.
  • width / height: Flexible canvas; common choices 1024×1024, 1536×1536, 1024×1536, 1536×1024.
  • seed: -1 for random, or set any integer for reproducible results.

How to Use

A) Text-to-Image

  1. Enter a prompt with subject + context + style + lighting + camera.
  2. Set width/height for your target aspect ratio (e.g., 1536×1536 for square).
  3. (Optional) Set seed for repeatability.
  4. Run and iterate on wording or seed.

B) Image-to-Image

  1. Upload an image.
  2. Write a prompt describing the desired change or style.
  3. (Optional) Set seed for repeatability.
  4. Run; tweak strength or prompt until the balance feels right.

Price

  • Per image for $0.0026.

Prompting Tips

  • Structure prompts as: [subject] + [context] + [style/artist] + [lighting] + [camera] + [mood].
  • For photorealism: “cinematic lighting, shallow depth of field, 50mm, natural skin texture.”
  • For products: “studio sweep, three-point lighting, soft reflections, high detail.”
  • Keep negative prompts concise: “blurry, extra fingers, watermark, text, low-res.”
  • Lock a seed once you like the look to iterate predictably.

Notes

  • SDXL will honor platform safety rules; if a prompt is blocked, simplify and try again.
  • Commercial use follows Stability AI licensing and WaveSpeedAI terms.

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/stability-ai/sdxl" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "size": "1024*1024",
    "seed": -1,
    "enable_base64_output": false
}'

# 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
promptstringYes-The positive prompt for the generation.
imagestringNo-The image to generate an image from.
sizestringNo1024*1024256 ~ 1536 per dimensionThe size of the generated media in pixels (width*height).
seedintegerNo-1-1 ~ 2147483647The random seed to use for the generation. -1 means a random seed will be used.
enable_base64_outputbooleanNofalse-If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API.

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.has_nsfw_contentsarrayArray of boolean values indicating NSFW detection for each output
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

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