GPT Image 1 Serverless API

Create high-quality AI-generated images from text prompts using OpenAI's GPT Image 1 model. Ideal for product design, content creation, and rapid visual prototyping at scale.

~48.18s
PlaygroundAPI
Pricing
POST /v2/gpt-image-1 · 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",
 9    prompt="Create a professional and visually engaging magazine cover for a lifestyle magazine called \"Urban Pulse.\" Include these featured article headlines clearly: \"10 Hidden Cafés You'll Love in NYC\" \"Minimalist Apartments: Small Spaces, Big Ideas\" \"Exclusive Interview: Behind the Scenes with Indie Band Echo District\" Use contemporary typography, vibrant colors, and include an eye-catching main photograph with a person standing in front of a city scene",
10    size="auto",
11    quality="auto",
12    moderation="auto",
13    background="opaque",
14    output_compression=100,
15    output_format="png",
16)
17print(result["status"])                      # COMPLETED
18print(result.get("output"))                  # model output (e.g. media URL)
19print(result["metrics"]["inference_time"])   # server compute seconds
20
21# --- Or submit + poll manually (track request_id, control the cadence) ---
22from segmind import SegmindClient, InferenceFailed, InferenceTimeout
23
24client = SegmindClient()                      # reads SEGMIND_API_KEY
25payload = {
26    "prompt": "Create a professional and visually engaging magazine cover for a lifestyle magazine called \"Urban Pulse.\" Include these featured article headlines clearly: \"10 Hidden Cafés You'll Love in NYC\" \"Minimalist Apartments: Small Spaces, Big Ideas\" \"Exclusive Interview: Behind the Scenes with Indie Band Echo District\" Use contemporary typography, vibrant colors, and include an eye-catching main photograph with a person standing in front of a city scene",
27    "size": "auto",
28    "quality": "auto",
29    "moderation": "auto",
30    "background": "opaque",
31    "output_compression": 100,
32    "output_format": "png",
33}
34job = client.submit_async("gpt-image-1", **payload)
35print(job.request_id)                         # available immediately
36try:
37    result = job.wait(timeout=600, interval=1.0)
38except InferenceTimeout as e:
39    print("still running:", e.request_id)
40except InferenceFailed as e:
41    print("failed:", e.detail)

API Endpoint

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

Parameters

promptrequired
string

Text prompt used to generate the image.

Default: "Create a professional and visually engaging magazine cover for a lifestyle magazine called \"Urban Pulse.\" Include these featured article headlines clearly: \"10 Hidden Cafés You'll Love in NYC\" \"Minimalist Apartments: Small Spaces, Big Ideas\" \"Exclusive Interview: Behind the Scenes with Indie Band Echo District\" Use contemporary typography, vibrant colors, and include an eye-catching main photograph with a person standing in front of a city scene"
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: Text/JSON

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

    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