Openai Gpt Image 2 Edit API Documentation

Openai Gpt Image 2 Edit API Documentation

Playground

OpenAI’s GPT Image 2 Edit enables image editing from natural-language instructions with one or more reference images. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

OpenAI GPT Image 2 Edit transforms one or more reference images using natural-language instructions. Upload your image, describe the changes you want, and the model generates a polished edited result with strong prompt alignment and production-ready quality.

• Need to generate a new image from scratch instead? Try OpenAI GPT Image 2 Text-to-Image.

> New: GPT Image 2.5 is available. The next generation adds two tiers, Flare (fast, balanced) and Sunburst (extra fidelity on intricate detail), five quality levels, and a lower default price of $0.039 per 1k image. Same request format, so switching is a model-ID change: GPT Image 2.5 Flare Edit · GPT Image 2.5 Sunburst Edit.

Why Choose This?

• Natural-language image editing Edit images by simply describing the changes you want in plain language — no manual masking or complex editing workflow required.

• Works with reference images Use one or more input images as the visual source for edits, transformations, or style adjustments.

• Flexible aspect ratios Generate edited outputs in square, portrait, or landscape formats for different publishing and design needs.

• Production-ready API Access the model through a ready-to-use REST inference API for easy integration into apps, tools, and creative pipelines.

• Fast and affordable Get high-quality image edits with simple usage-based pricing and no cold-start friction.

Parameters

How to Use

1. Upload reference images — add up to 16 images you want to edit.
2. Write your prompt — clearly describe the changes, style adjustments, or composition edits you want.
3. Choose aspect ratio (optional) — use 1:1 for square, 2:3 or 9:16 for portrait, 3:2 or 16:9 for landscape, etc. Auto-detected from input image if not specified.
4. Submit — run the model and download your edited image.

Example Prompt

Turn this product photo into a premium studio advertisement with soft cinematic lighting, a clean beige background, subtle shadows, realistic reflections, and luxury brand aesthetics

Pricing

Pricing varies by quality and resolution.

Prices below include one input image. Each additional input image adds $0.012.

Best Use Cases

• Product photo enhancement — Upgrade basic product shots into premium marketing visuals.
• Creative retouching — Change backgrounds, lighting, styling, or composition with natural-language instructions.
• Marketing adaptation — Rework existing brand assets into new campaign visuals without recreating them from scratch.
• Social media content — Quickly edit images into platform-ready formats for posts, ads, and promos.
• Design iteration — Explore multiple visual directions from the same base image with different prompts.
• E-commerce optimization — Improve product presentation for listings, hero banners, and promotional creatives.

Pro Tips

• Be specific about what should stay unchanged and what should be modified.
• Mention visual style clearly, such as photorealistic, luxury editorial, minimal, cinematic, or flat lay.
• Describe lighting, background, framing, and mood for more controllable results.
• Use concise but precise prompts instead of overly vague instructions like “make it better.”
• Try multiple aspect ratios when adapting the same edit for different placements.
• If using multiple reference images, make sure they are visually clear and relevant to the intended output.

Notes

• Both images and prompt are required fields.
• Supported aspect ratios are 1:1, 3:2, 2:3, 3:4, 4:3, 4:5, 5:4, 9:16, 16:9, and 21:9. Auto-detected from input image if not specified.
• This model is intended for image editing based on reference images and natural-language instructions.

Related Models

• OpenAI GPT Image 2 Text-to-Image — Generate new images directly from natural-language prompts.

• OpenAI GPT Image 2.5 Flare Edit — Next generation, fast and balanced tier with five quality levels.

• OpenAI GPT Image 2.5 Sunburst Edit — Next generation, precision-focused tier for intricate detail.

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",
  "images": [
    "https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
  ],
  "aspect_ratio": "1:1",
  "resolution": "1k",
  "quality": "medium",
  "output_format": "png"
}
JSON
)

# 1. Submit the prediction once. Never retry this request automatically:
# a retry after an unclear failure can create a second, billed task.
CHECK='The task may already exist. Check History or the predictions list before submitting again.'
if ! SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  --connect-timeout 10 --max-time 60 \
  -X POST "https://api.wavespeed.ai/api/v3/openai/gpt-image-2/edit" \
  -H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  -H "Content-Type: application/json" \
  -d "${REQUEST_BODY}"); then
  printf 'Submit failed. %s\n' "${CHECK}" >&2
  exit 1
fi

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 "${PREDICTION_ID}" ]; then
  printf 'Submission response did not contain a prediction id. %s\n' "${CHECK}" >&2
  exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"

# 2. Poll until the prediction reaches a final status.
BODY_FILE=$(mktemp)
trap 'rm -f "${BODY_FILE}"' EXIT
while true; do
  # Transient errors (429, 5xx) are retried, honoring Retry-After.
  HTTP_CODE=$(curl --silent --show-error --fail-with-body \
    --connect-timeout 10 --max-time 60 --retry 5 --retry-delay 2 \
    --output "${BODY_FILE}" --write-out '%{http_code}' \
    "${RESULT_URL}" \
    -H "Authorization: Bearer ${WAVESPEED_API_KEY}" || true)
  case "${HTTP_CODE}" in
    2??) ;;
    000|429|5??)  # dropped connection or temporary error: keep polling
      printf 'Task %s: HTTP %s, polling again in 10s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
      sleep 10; continue ;;
    *) printf 'Task %s: HTTP %s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
      cat "${BODY_FILE}" >&2; exit 1 ;;
  esac
  RESULT=$(jq 'if type == "object" and has("data") then .data else . end' "${BODY_FILE}")
  STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')

  case "${STATUS}" in
    completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
    failed|cancelled|timeout|deleted)
      printf 'Task %s ended with status %s\n' "${PREDICTION_ID}" "${STATUS}" >&2
      printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
    *) sleep 2 ;;
  esac
done

Parameters

Task Submission Parameters

Request Parameters

Response Parameters

Result Request Parameters

Result Response Parameters