Image Generation Guide

modelsok offers several AI image models. The base URL is https://modelsok.com, authenticated with Authorization: Bearer <API Key>. This page explains how to call each model and shares practical tips.

Available models

GPT Image 2.5: Sunburst / Flare

Both models use the same endpoint and authentication. Switch models by changing only model. Text-to-image requests were verified on both serving channels on September 9, 2026. The example below uses the verified minimal parameters. Check your account's model catalog for availability and pricing.

curl --max-time 300 https://modelsok.com/v1/images/generations \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-2.5-sunburst",
    "prompt": "An orange ceramic robot holding a sunflower against a blue background, studio product photography",
    "n": 1,
    "size": "1024x1024"
  }'

For Flare, change model to gpt-image-2.5-flare. The synchronous response contains Base64 image data in data[0].b64_json; decode it to save a PNG. The example omits response_format and quality.

Use asynchronous submission for long-running requests

Append ?async=true to the submission URL to receive a task id. Poll with the same API key:

curl "https://modelsok.com/v1/tasks/$TASK_ID" \
  -H "Authorization: Bearer $API_KEY"

Poll every 3–5 seconds. Keep waiting while state is queued or processing; read image results from data.images when it is succeeded, and inspect error details when it is failed. Asynchronous results differ from the synchronous data[].b64_json structure. Save the task ID and resume polling after a query timeout instead of submitting another billable generation.

A 300-second client timeout does not extend the CDN timeout. Prefer asynchronous submission when encountering HTTP 524.

If data.images[].url is a relative path (for example, /api/relay-temp-images/…png), resolve it against https://modelsok.com before downloading. Download and save the image promptly; temporary image URLs are not permanent storage.

gpt-image-2

Size rules

The output size exactly matches the requested size. That size must satisfy all three conditions below, otherwise the API returns an explicit error (it never silently falls back to a different size):

Common sizes:

Quality tiers

The optional quality parameter accepts low / medium / high and defaults to low. It affects quality, latency and price at the same time, so specify it explicitly based on your use case.

Text to image

curl https://modelsok.com/v1/images/generations \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-2",
    "prompt": "a red panda eating bamboo, flat vector illustration",
    "size": "1024x1024",
    "quality": "medium"
  }'

Image to image / editing

Pass a publicly reachable image URL in the image field — no file upload needed. Pass an array to submit multiple reference images (up to 16).

curl https://modelsok.com/v1/images/edits \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-2",
    "prompt": "make the mug matte black, keep the composition unchanged",
    "image": "https://your-cdn/reference.png",
    "size": "3840x2160",
    "quality": "medium"
  }'

Response example:

{
  "created": 1780888000,
  "data": [{ "b64_json": "iVBORw0KGgoAAAANSUhEUgAA..." }]
}

Python example

import base64, requests

resp = requests.post(
    "https://modelsok.com/v1/images/edits",
    headers={"Authorization": f"Bearer {API_KEY}"},
    json={
        "model": "gpt-image-2",
        "prompt": "a red panda eating bamboo, flat vector illustration",
        "image": "https://your-cdn/reference.png",
        "size": "2048x2048",
        "quality": "medium",
    },
    timeout=300,
)
data = resp.json()["data"][0]["b64_json"]
open("out.png", "wb").write(base64.b64decode(data))

A single image-to-image call typically takes 20–110 seconds (longer at higher quality). Set your client timeout to at least 300 seconds and add retries.

Gemini models

Option 1: OpenAI-compatible endpoint

Works for gemini-2.5-flash-image-preview.

curl https://modelsok.com/v1/images/generations \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemini-2.5-flash-image-preview",
    "prompt": "a red panda eating bamboo, flat vector illustration",
    "n": 1,
    "size": "1024x1024",
    "response_format": "b64_json"
  }'

Prefer response_format: "b64_json". The default url returns a temporary object-storage link that may expire and occasionally times out on download. Using b64_json gives you the image data directly and is more robust to integrate. This parameter is available for Gemini models only — gpt-image-2 does not support it.

Option 2: Gemini native endpoint

Works for all Gemini image models. Note the trailing slash in the path.

curl "https://modelsok.com/v1beta/models/gemini-2.5-flash-image:generateContent/" \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [{ "parts": [{ "text": "a blue cartoon cat, white background" }] }]
  }'

Note: the Gemini native endpoint usually returns the image as a Markdown image link embedded in text (under candidates[0].content.parts[].text, like ![image](https://...)) rather than as inlineData. Extract the URL from the text and download it. To get standard image data directly, use gemini-2.5-flash-image-preview via the OpenAI-compatible endpoint instead.

Response example:

{
  "candidates": [{
    "content": {
      "role": "model",
      "parts": [{ "text": "![image](https://.../xxxx.png)" }]
    }
  }]
}

Billing

gpt-image-2 is billed by token usage — the cost depends on the output size (size), the quality tier (quality) and the reference image size. Larger outputs and higher tiers cost more. The other image models are billed per call (a fixed amount per generation).

See the Model Marketplace for exact prices, which vary by account tier.