GPT Image 2.6 Sunburst · Token · API

Quick start

Three steps: submit a job, poll it, take the image link. Replace YOUR_API_KEY with your key and the commands below run as they are.

Step 1 · Submit (returns a job id at once, HTTP 202)

curl https://kovapi.com/v1/images/generations \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "gpt-image-2.6-sunburst-token", "prompt": "An oil painting of a harbour at dusk, visible brushstrokes, warm palette", "size": "16:9", "resolution": "2K"}'

Response (HTTP 202)

{
  "id": "img_7f3c9a1e2b4d6f8a0c1e3b5d",
  "object": "image.generation.job",
  "status": "queued",
  "created": 1791281400,
  "model": "gpt-image-2.6-sunburst-token"
}

Step 2 · Poll every 2–3 seconds until status is succeeded or failed

curl https://kovapi.com/v1/images/jobs/img_7f3c9a1e2b4d6f8a0c1e3b5d \
  -H "Authorization: Bearer YOUR_API_KEY"

Response when it succeeds

{
  "id": "img_7f3c9a1e2b4d6f8a0c1e3b5d",
  "object": "image.generation.job",
  "status": "succeeded",
  "created": 1791281400,
  "model": "gpt-image-2.6-sunburst-token",
  "data": [
    {"url": "https://img.kovapi.com/i/2be8cd16d37f3a4b9c0e1f2a3b4c5d6e.png"}
  ],
  "usage": {"images": 1, "resolution": "2K", "model": "gpt-image-2.6-sunburst-token"}
}

Step 3 · data[0].url is the image (PNG). It is kept for 15 days; download it to your own storage to keep it longer.

Complete example (Python: submit, wait, save to disk)

import time
import requests

BASE = "https://kovapi.com/v1"
HEADERS = {"Authorization": "Bearer YOUR_API_KEY"}

# 1. submit
job = requests.post(f"{BASE}/images/generations", headers=HEADERS, json={
    "model": "gpt-image-2.6-sunburst-token",
    "prompt": "An oil painting of a harbour at dusk, visible brushstrokes, warm palette",
    "size": "16:9",
    "resolution": "2K",
}).json()
if "error" in job:
    raise SystemExit(job["error"]["message"])

# 2. poll every 3 seconds until it finishes
while job["status"] not in ("succeeded", "failed"):
    time.sleep(3)
    job = requests.get(f"{BASE}/images/jobs/{job['id']}", headers=HEADERS).json()

# 3. download the image
if job["status"] == "succeeded":
    url = job["data"][0]["url"]
    with open("gpt-image-2.6-sunburst-token.png", "wb") as f:
        f.write(requests.get(url).content)
    print("saved", url)
else:
    print("failed:", job["error"]["code"], job["error"]["message"])

Authentication

Authorization: Bearer YOUR_API_KEY
Content-Type: application/json

Create an API Key in the console to start.

Request parameters

The JSON body of POST /v1/images/generations:

background may be transparent (pair it with PNG or WebP output); output_format is png (default), jpeg or webp. n must be 1. A parameter not listed here returns 400 unsupported_image_parameter at submit and nothing is charged; the result comes back as url, and usage carries this job's tokens and charge.

Billed by tokens

At submit, an upper bound is held from the size, quality and number of references; after the image is made the job settles on the usage OpenAI reports, and the rest of the hold is returned at once; a failure is refunded in full. Prices per 1M tokens:

Measured output tokens and cost (input not included)

For the same size and quality the output tokens are the same every time, whatever the prompt; each reference adds about 700-1,600 image input tokens.

Aspect ratio, resolution and output size

Put the ratio in size and the tier in resolution. You get the original image as generated, neither cropped nor resized, at the sizes below: both sides are multiples of 16, and 4K stays within 3840 px a side and about 8.3 megapixels.

• The 15 ratios in the table are supported; any other ratio returns 400 at submit and nothing is charged. With size set to auto and a reference image, the picture follows the ratio closest to the first reference; without one it is 1:1. A few long, narrow ratios at 1K are below the model's minimum pixel count and render at the enlarged sizes in the table (16:9 is 1088×608).
• size may also be a pixel size (e.g. 1536x1024) in one of the 15 ratios: width and height are rounded down to multiples of 16, scaled down when above the tier's limit and scaled up to the model's minimum (about 655,000 pixels) when too small. The tier comes from resolution; without it, from the long side: up to 1536 is 1K, up to 2048 is 2K, larger is 4K. Long-side ranges: 1K 512-1536, 2K 2016-2304, 4K 2049-4096; outside them the request returns 400 at submit and nothing is charged.

Quality and native resolution

• Without quality the image renders at medium. Quality changes only the tokens and the price, never the size; with auto the model decides, the hold assumes max, and the job settles on the real usage.
• If quality holds 1K, 2K or 4K and resolution is not given, it is read as the resolution tier (size and price follow that tier).
• At busy times jobs wait in the queue instead of failing at once; if no image comes after a long wait (about 15 minutes) the job fails and is refunded in full, and you can resubmit it as is.

Image-to-image and reference images

• Send image (one) or images (several, up to 16; any beyond that are not used) for image-to-image, and say in the prompt what to change. POST /v1/images/edits takes the same parameters.
• Both endpoints take a JSON body only, not a multipart file upload, so the OpenAI SDK's images.edit() cannot be used as is: pass links or base64 as in the example below.
• Each reference may be a public image link (http / https), a data: URI or plain base64, up to 16 MB, in PNG, JPEG or WebP; a reference in any other format fails the job and the hold is refunded in full.
• A URL has to download the image itself: not a web page, and not behind a login or hotlink protection. A reference we cannot read is refused at submit with a 400 that says which one and why; no job is created and nothing is charged.
• The output ratio comes from size, not from the reference. To keep the original ratio, set size to it.
• We host the references for you and keep them for 7 days.

Image-to-image with two references

curl https://kovapi.com/v1/images/generations \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "gpt-image-2.6-sunburst-token", "prompt": "Keep the people, change the background to a beach at night with warm string lights", "images": ["https://example.com/people.jpg", "https://example.com/beach.jpg"], "size": "3:4", "resolution": "2K"}'

Job status and fields

GET /v1/images/jobs/{id} reports these statuses; every field is described in Async jobs. Poll every 2–3 seconds, or use a webhook.

One account runs up to 50 jobs at a time; further jobs wait in submission order, and a job that has not started after 15 minutes fails and is refunded in full. Job records are kept for 3 days and image links for 15 days.

How long it takes

Usually 20–60 seconds from submit to result; 4K, edits with several references and busy periods take longer, and an occasional job takes a minute or two.

Errors and refunds

An error at submit comes back at once as HTTP 4xx / 5xx: no job is created and nothing is charged. A failure after the job was accepted is reported by the job endpoint, and the hold is refunded in full. Every code is listed under Error codes.

Errors at submit

Failed jobs (status failed)

Webhooks instead of polling

Add callback_url when you submit and the moment the job ends, success or failure, the gateway pushes exactly what the poll endpoint returns to that URL, signed and retried on failure. You can also set an account-wide address under Settings → Webhook in the console. Webhook docs →

curl https://kovapi.com/v1/images/generations \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "gpt-image-2.6-sunburst-token", "prompt": "An oil painting of a harbour at dusk, visible brushstrokes, warm palette", "size": "1:1", "callback_url": "https://your-domain.com/webhook"}'