GPT Image 1 Edit Serverless API

Edit and compose images using natural language with GPT Image 1 Edit, OpenAI’s powerful inpainting and multi-reference editing model. Perfect for marketing visuals, product updates, and creative asset generation.

~56.79s
PlaygroundAPI
Pricing
POST /v2/gpt-image-1-edit · submit + poll
 1# pip install "segmind>=1.1.0"
 2# export SEGMIND_API_KEY="YOUR_API_KEY"
 3import segmind
 4
 5# Async (v2): submit to the queue and block until COMPLETED.
 6# run() returns the final result dict (600s deadline, 1.0s poll by default).
 7result = segmind.run(
 8    "gpt-image-1-edit",
 9    prompt="Make a picture of a 3D action figure toy, named 'Teena'. Display it in transparent blister packaging with 'Teena' in white text at the top. Action figure wears a trendy, chic outfit featuring a stylish crop top with high-waisted skinny jeans and fashionable heels. Include accessories: a smartphone with selfie stick, a small ring light, and a designer handbag beside the figure. Use minimalist cardboard packaging design in cute toy store style. Cartoonish, cute yet neat appearance.",
10    image_urls=["https://segmind-resources.s3.amazonaws.com/output/cf5d6d3d-9be2-4538-b6b2-3d8ff11594b9-Beach-walk.png"],
11    mask=None,
12    size="auto",
13    quality="auto",
14    background="opaque",
15    output_compression=100,
16    output_format="png",
17    moderation="auto",
18)
19print(result["status"])                      # COMPLETED
20print(result.get("output"))                  # model output (e.g. media URL)
21print(result["metrics"]["inference_time"])   # server compute seconds
22
23# --- Or submit + poll manually (track request_id, control the cadence) ---
24from segmind import SegmindClient, InferenceFailed, InferenceTimeout
25
26client = SegmindClient()                      # reads SEGMIND_API_KEY
27payload = {
28    "prompt": "Make a picture of a 3D action figure toy, named 'Teena'. Display it in transparent blister packaging with 'Teena' in white text at the top. Action figure wears a trendy, chic outfit featuring a stylish crop top with high-waisted skinny jeans and fashionable heels. Include accessories: a smartphone with selfie stick, a small ring light, and a designer handbag beside the figure. Use minimalist cardboard packaging design in cute toy store style. Cartoonish, cute yet neat appearance.",
29    "image_urls": ["https://segmind-resources.s3.amazonaws.com/output/cf5d6d3d-9be2-4538-b6b2-3d8ff11594b9-Beach-walk.png"],
30    "mask": None,
31    "size": "auto",
32    "quality": "auto",
33    "background": "opaque",
34    "output_compression": 100,
35    "output_format": "png",
36    "moderation": "auto",
37}
38job = client.submit_async("gpt-image-1-edit", **payload)
39print(job.request_id)                         # available immediately
40try:
41    result = job.wait(timeout=600, interval=1.0)
42except InferenceTimeout as e:
43    print("still running:", e.request_id)
44except InferenceFailed as e:
45    print("failed:", e.detail)

API Endpoint

POSThttps://api.segmind.com/v1/gpt-image-1-edit

Parameters

image_urlsrequired
string[]

A list of images.

maskrequired
string (uri)

Input Image.

promptrequired
string

Text prompt used to generate the image.

Default: ""
backgroundoptional
string

Select whether the image background should be transparent or opaque.

Default: "opaque"
Allowed values :
"transparent""opaque"
moderationoptional
string

Controls the moderation strictness - use low for less restrictions.

Default: "auto"
Allowed values :
"low""auto"
output_compressionoptional
integer

Select the compression level for the output image (1-100).

Default: 100
output_formatoptional
string

Select the output format of the image.

Default: "png"
Allowed values :
"png""jpeg""webp"
qualityoptional
string

Controls the visual quality of the output image.

Default: "auto"
Allowed values :
"low""medium""high""auto"
sizeoptional
string

Select image resolution. Square is the fastest to generate.

Default: "auto"
Allowed values :
"1024x1024""1536x1024""1024x1536""auto"

Response Type

Returns: Image

Asynchronous requests (v2)

Use Async for video, long-running (>~60s), or high-concurrency workloads; Sync is simplest for fast image & LLM calls. Async submits a request and you poll it to completion.

  1. 1
    POST /v2/gpt-image-1-edit

    Submit — returns request_id, status_url, response_url

  2. 2
    GET /v2/requests/{id}/status

    Poll — until COMPLETED or FAILED

  3. 3
    GET /v2/requests/{id}

    Result — final response body

Status states

QUEUED— Accepted, waiting for a worker
PROCESSING— Running on a worker
COMPLETED— Done — result body is ready
FAILED— Errored (incl. content/RAI blocks)
  • A FAILED request is served as HTTP 422 — the body still carries the error detail.
  • An unknown or expired request_id returns HTTP 404.
  • Results are retained for 1 hour, then expire.
  • Content / RAI blocks surface as FAILED, not a separate state.
  • Track completion by polling the status endpoint.

Common Error Codes

The API returns standard HTTP status codes. Detailed error messages are provided in the response body.

400

Bad Request

Invalid parameters or request format

401

Unauthorized

Missing or invalid API key

403

Forbidden

Insufficient permissions

404

Not Found

Model or endpoint not found

406

Insufficient Credits

Not enough credits to process request

429

Rate Limited

Too many requests

500

Server Error

Internal server error

502

Bad Gateway

Service temporarily unavailable

504

Timeout

Request timed out