Step1x Edit

Step1x Edit

Playground

Try it on WaveSpeedAI!

Step1X-Edit converts photos into professional-quality edits using simple instructions, rivaling top proprietary tools. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Step1X Edit is a powerful AI-powered image editing model that modifies images based on simple text instructions. Describe what you want to change — hair color, clothing, background, objects — and the model applies precise, targeted edits while preserving the rest of the image.


Why It Stands Out

  • Instruction-based editing: Edit images using natural language commands.
  • Precise modifications: Changes only what you specify, preserving everything else.
  • Prompt Enhancer: Built-in AI-powered prompt optimization for better results.
  • Negative prompt support: Exclude unwanted elements for cleaner outputs.
  • Fine-tuned control: Adjust guidance scale and inference steps for precise results.
  • Affordable pricing: High-quality edits at just $0.03 per image.
  • Reproducibility: Use the seed parameter to recreate exact results.

Parameters

ParameterRequiredDescription
promptYesText instruction describing the edit you want to make.
imageYesSource image to edit (upload or public URL).
negative_promptNoElements to avoid in the output.
seedNoSet for reproducibility; leave empty for random.
guidance_scaleNoPrompt adherence strength (default: 4).
num_inference_stepsNoQuality/speed trade-off (default: 30).

How to Use

  1. Upload your image — drag and drop a file or paste a public URL.
  2. Write an editing instruction describing what you want to change. Use the Prompt Enhancer for AI-assisted optimization.
  3. Add a negative prompt (optional) — specify elements to exclude.
  4. Adjust parameters (optional) — fine-tune guidance scale and inference steps.
  5. Click Run and download your edited image.

Example Instructions

  • “Change hair color to red”
  • “Add sunglasses”
  • “Change the background to a beach”
  • “Make the dress blue”
  • “Remove the hat”
  • “Add a smile”
  • “Change season to winter”

Best Use Cases

  • Portrait Retouching — Change hair color, add accessories, modify expressions.
  • Fashion & E-commerce — Swap clothing colors, add or remove items.
  • Background Editing — Change environments and settings.
  • Creative Projects — Experiment with visual variations quickly.
  • Content Creation — Generate multiple versions of images for A/B testing.

Pricing

OutputPrice
Per image$0.03

Pro Tips for Best Quality

  • Use clear, specific instructions — “Change hair color to red” works better than “Make it different.”
  • Keep instructions focused on one or two changes at a time.
  • Use negative prompts to prevent unwanted side effects.
  • Lower guidance scale (2–4) for subtle changes, higher (5–7) for more dramatic edits.
  • Fix the seed when iterating to compare different instructions on the same base.

Notes

  • Ensure uploaded image URLs are publicly accessible.
  • Processing time varies based on current queue load.
  • Please ensure your content complies with usage guidelines.

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",
  "image": "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg",
  "guidance_scale": 4,
  "num_inference_steps": 30
}
JSON
)

# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  -X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/step1x-edit" \
  -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.
imagestringYes-The image URL to generate an image from. Needs to match the dimensions of the mask.
negative_promptstringNo-The negative prompt for the generation.
seedintegerNo--The random seed to use for the generation.
guidance_scalenumberNo40 ~ 20The guidance scale to use for the generation.
num_inference_stepsintegerNo301 ~ 50The number of inference steps to perform.

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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