IMAGE API

GPT Image 2.6 Flare · Reference image edits

Use Flare to iterate on illustrations and product visuals. Reference image edits · NewRouters Images API

POST/v1/tasksMODELgpt-image-2.6-flare

Official reference gpt-image-2.6-flareChecked 2026-11-05Official docs

Code examples & responses

Request & responseExamples

POST/v1/tasks

Server-side request

curl "https://newrouters.com/v1/tasks" \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  --data '{
  "model": "gpt-image-2.6-flare",
  "input": {
    "prompt": "Change the cup to blue. Preserve the handle and background.",
    "size": "auto",
    "quality": "low",
    "output_format": "jpeg",
    "images": [
      "https://example.com/cup.png"
    ]
  }
}'

Server-side request

const apiBaseUrl = "https://newrouters.com";
const apiKey = process.env.API_KEY;
if (!apiKey) throw new Error("Set API_KEY in your server environment");

const response = await fetch(apiBaseUrl + "/v1/tasks", {
  method: "POST",
  headers: {
    "Content-Type": "application/json",
    "Authorization": "Bearer " + apiKey
  },
  body: JSON.stringify({
  "model": "gpt-image-2.6-flare",
  "input": {
    "prompt": "Change the cup to blue. Preserve the handle and background.",
    "size": "auto",
    "quality": "low",
    "output_format": "jpeg",
    "images": [
      "https://example.com/cup.png"
    ],
    "resolution": "2k"
  }
})
});

const result = await response.json();
if (!response.ok) throw new Error(JSON.stringify(result));
console.log(result);

Server-side request

import json
import os
from urllib.request import Request, urlopen

api_base_url = "https://newrouters.com"
api_key = os.environ["API_KEY"]
body = json.loads("{\"model\":\"gpt-image-2.6-flare\",\"input\":{\"prompt\":\"Change the cup to blue. Preserve the handle and background.\",\"size\":\"auto\",\"quality\":\"low\",\"output_format\":\"jpeg\",\"images\":[\"https://example.com/cup.png\"],\"resolution\":\"2k\"}}")

request = Request(
    api_base_url + "/v1/tasks",
    data=json.dumps(body).encode("utf-8"),
    headers={
    "Content-Type": "application/json",
    "Authorization": "Bearer " + api_key
    },
    method="POST",
)
with urlopen(request) as response:
    print(json.load(response))

The API origin is filled in. Set API_KEY before running. Examples never submit automatically.

ResponseSelected fields · illustrative values

202Task accepted

JSON

{
  "id": "TASK_ID",
  "status": "pending",
  "model": "gpt-image-2.6-flare",
  "result": null,
  "error": null
}

200Successful result

JSON

{
  "id": "TASK_ID",
  "status": "succeeded",
  "model": "gpt-image-2.6-flare",
  "result": {
    "assets": [
      "https://example.com/output.png"
    ]
  },
  "error": null
}

Retrieve results after submission

Request lifecycleAsynchronous media

Create a task01
POST /v1/tasks
Submit model + input. Save the returned task id.
202 · pending
Poll status02
GET /v1/tasks/{id}
Wait and poll again while pending or processing.
Wait → poll again
Read the outcome03
result.assets[] / error
Read the result for the terminal task state.
succeeded→ assetsfailed→ error

Use Flare to iterate on illustrations and product visuals. Use the NewRouters model ID gpt-image-2.6-flare.

API guide · Text to image

Replace the example URL in input.images with an accessible reference image. Describe the change and what to preserve. Choose JPEG, PNG or WebP for edits.

curl "https://newrouters.com/v1/tasks" \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  --data '{
  "model": "gpt-image-2.6-flare",
  "input": {
    "prompt": "Change the cup to blue. Preserve the handle and background.",
    "size": "auto",
    "quality": "low",
    "output_format": "jpeg",
    "images": [
      "https://example.com/cup.png"
    ]
  }
}'

Save the task ID and poll GET /v1/tasks/{id} with the same key. On success, download the file from result.assets.

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