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GPT-Image-2 图像生成

  • 异步处理模式,返回任务ID用于后续查询
  • 基于 OpenAI Images 兼容协议,支持文生图 / 图生图
  • 支持 15 种图片比例,通过 size 字段传入
  • 通过 resolution(1k / 2k / 4k)控制实际输出像素档位
  • 参考图最多 15 张,支持 URL 与 base64 混填
  • 按分辨率档位(1K / 2K / 4K)计费

模型名兼容提示:本接口同时兼容别名 gpt-image-2-ext,它等价于 gpt-image-2,两者可互换使用、效果一致。

请求示例
# model 可填 "gpt-image-2",也兼容别名 "gpt-image-2-ext"
curl --request POST \
  --url https://26j.cn/v1/images/generations \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "gpt-image-2",
    "prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
    "n": 1,
    "size": "16:9",
    "resolution": "2k"
  }'
import requests

url = "https://26j.cn/v1/images/generations"

payload = {
    "model": "gpt-image-2",
    "prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
    "n": 1,
    "size": "16:9",
    "resolution": "2k"
}

headers = {
    "Authorization": "Bearer <token>",
    "Content-Type": "application/json"
}

response = requests.post(url, json=payload, headers=headers)

print(response.json())
const url = "https://26j.cn/v1/images/generations";

const payload = {
  model: "gpt-image-2",
  prompt: "一只橘猫坐在窗台上看夕阳,水彩画风格",
  n: 1,
  size: "16:9",
  resolution: "2k"
};

const headers = {
  "Authorization": "Bearer <token>",
  "Content-Type": "application/json"
};

fetch(url, {
  method: "POST",
  headers: headers,
  body: JSON.stringify(payload)
})
  .then(response => response.json())
  .then(data => console.log(data))
  .catch(error => console.error('Error:', error));
package main

import (
    "bytes"
    "encoding/json"
    "fmt"
    "io/ioutil"
    "net/http"
)

func main() {
    url := "https://26j.cn/v1/images/generations"

    payload := map[string]interface{}{
        "model":      "gpt-image-2",
        "prompt":     "一只橘猫坐在窗台上看夕阳,水彩画风格",
        "n":          1,
        "size":       "16:9",
        "resolution": "2k",
    }

    jsonData, _ := json.Marshal(payload)

    req, _ := http.NewRequest("POST", url, bytes.NewBuffer(jsonData))
    req.Header.Set("Authorization", "Bearer <token>")
    req.Header.Set("Content-Type", "application/json")

    client := &http.Client{}
    resp, err := client.Do(req)
    if err != nil {
        panic(err)
    }
    defer resp.Body.Close()

    body, _ := ioutil.ReadAll(resp.Body)
    fmt.Println(string(body))
}
import java.net.http.HttpClient;
import java.net.http.HttpRequest;
import java.net.http.HttpResponse;
import java.net.URI;

public class Main {
    public static void main(String[] args) throws Exception {
        String url = "https://26j.cn/v1/images/generations";

        String payload = """
        {
          "model": "gpt-image-2",
          "prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
          "n": 1,
          "size": "16:9",
          "resolution": "2k"
        }
        """;

        HttpClient client = HttpClient.newHttpClient();
        HttpRequest request = HttpRequest.newBuilder()
            .uri(URI.create(url))
            .header("Authorization", "Bearer <token>")
            .header("Content-Type", "application/json")
            .POST(HttpRequest.BodyPublishers.ofString(payload))
            .build();

        HttpResponse<String> response = client.send(request,
            HttpResponse.BodyHandlers.ofString());

        System.out.println(response.body());
    }
}
<?php

$url = "https://26j.cn/v1/images/generations";

$payload = [
    "model" => "gpt-image-2",
    "prompt" => "一只橘猫坐在窗台上看夕阳,水彩画风格",
    "n" => 1,
    "size" => "16:9",
    "resolution" => "2k"
];

$ch = curl_init($url);
curl_setopt($ch, CURLOPT_RETURNTRANSFER, true);
curl_setopt($ch, CURLOPT_POST, true);
curl_setopt($ch, CURLOPT_POSTFIELDS, json_encode($payload));
curl_setopt($ch, CURLOPT_HTTPHEADER, [
    "Authorization: Bearer <token>",
    "Content-Type: application/json"
]);

$response = curl_exec($ch);
curl_close($ch);

echo $response;
?>
require 'net/http'
require 'json'
require 'uri'

url = URI("https://26j.cn/v1/images/generations")

payload = {
  model: "gpt-image-2",
  prompt: "一只橘猫坐在窗台上看夕阳,水彩画风格",
  n: 1,
  size: "16:9",
  resolution: "2k"
}

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Post.new(url)
request["Authorization"] = "Bearer <token>"
request["Content-Type"] = "application/json"
request.body = payload.to_json

response = http.request(request)
puts response.body
import Foundation

let url = URL(string: "https://26j.cn/v1/images/generations")!

let payload: [String: Any] = [
    "model": "gpt-image-2",
    "prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格",
    "n": 1,
    "size": "16:9",
    "resolution": "2k"
]

var request = URLRequest(url: url)
request.httpMethod = "POST"
request.setValue("Bearer <token>", forHTTPHeaderField: "Authorization")
request.setValue("application/json", forHTTPHeaderField: "Content-Type")
request.httpBody = try? JSONSerialization.data(withJSONObject: payload)

let task = URLSession.shared.dataTask(with: request) { data, response, error in
    if let error = error {
        print("Error: \(error)")
        return
    }

    if let data = data, let responseString = String(data: data, encoding: .utf8) {
        print(responseString)
    }
}

task.resume()
using System;
using System.Net.Http;
using System.Text;
using System.Threading.Tasks;

class Program
{
    static async Task Main(string[] args)
    {
        var url = "https://26j.cn/v1/images/generations";

        var payload = @"{
            ""model"": ""gpt-image-2"",
            ""prompt"": ""一只橘猫坐在窗台上看夕阳,水彩画风格"",
            ""n"": 1,
            ""size"": ""16:9"",
            ""resolution"": ""2k""
        }";

        using var client = new HttpClient();
        client.DefaultRequestHeaders.Add("Authorization", "Bearer <token>");

        var content = new StringContent(payload, Encoding.UTF8, "application/json");
        var response = await client.PostAsync(url, content);
        var result = await response.Content.ReadAsStringAsync();

        Console.WriteLine(result);
    }
}
import 'dart:convert';
import 'package:http/http.dart' as http;

void main() async {
  final url = Uri.parse('https://26j.cn/v1/images/generations');

  final payload = {
    'model': 'gpt-image-2',
    'prompt': '一只橘猫坐在窗台上看夕阳,水彩画风格',
    'n': 1,
    'size': '16:9',
    'resolution': '2k'
  };

  final response = await http.post(
    url,
    headers: {
      'Authorization': 'Bearer <token>',
      'Content-Type': 'application/json'
    },
    body: jsonEncode(payload),
  );

  print(response.body);
}
library(httr)
library(jsonlite)

url <- "https://26j.cn/v1/images/generations"

payload <- list(
  model = "gpt-image-2",
  prompt = "一只橘猫坐在窗台上看夕阳,水彩画风格",
  n = 1,
  size = "16:9",
  resolution = "2k"
)

response <- POST(
  url,
  add_headers(
    Authorization = "Bearer <token>",
    `Content-Type` = "application/json"
  ),
  body = toJSON(payload, auto_unbox = TRUE),
  encode = "raw"
)

cat(content(response, "text"))
响应示例
{
  "code": 200,
  "data": [
    {
      "status": "submitted",
      "task_id": "task_01KPQ7J7DWB7QZ3WCEK3YVPBRA"
    }
  ]
}
{
  "error": {
    "code": 400,
    "message": "参数错误:size 不合法 / resolution 不支持 / 像素违规等",
    "type": "invalid_request_error"
  }
}
{
  "error": {
    "code": 401,
    "message": "身份验证失败,请检查您的API密钥",
    "type": "authentication_error"
  }
}
{
  "error": {
    "code": 402,
    "message": "账户余额不足,请充值后再试",
    "type": "payment_required"
  }
}
{
  "error": {
    "code": 429,
    "message": "请求过于频繁,请稍后再试",
    "type": "rate_limit_error"
  }
}
{
  "error": {
    "code": 500,
    "message": "服务器错误",
    "type": "server_error"
  }
}
{
  "error": {
    "code": 503,
    "message": "上游暂时不可用,请稍后再试",
    "type": "service_unavailable"
  }
}

Authorizations

Authorizationstring必填

所有接口均需要使用 Bearer Token 进行认证

获取 API Key:

访问 API Key 管理页面 获取您的 API Key

使用时在请求头中添加:

Authorization: Bearer YOUR_API_KEY

Body

modelstring必填默认 gpt-image-2

图像生成模型名称

固定填写 gpt-image-2(兼容别名 gpt-image-2-ext)

为兼容旧版调用,别名 gpt-image-2-ext(对应 gpt-image-2)仍可正常使用。

nsfw_checkboolean默认 false

是否在提交图片任务前执行内容审核。

  • true:使用 omni-moderation-latest 审核提示词和输入图片
  • false 或不传:不发起审核请求,不增加审核成本与延迟(默认)
promptstring必填

图像生成的文本描述

  • 支持中英文,建议详细描述
  • 提交前会经过平台敏感词 / 安全审核,命中违规内容会直接返回错误
ninteger默认 1

生成图片张数

取值:1

必须传入纯数字(如 1),不要加引号

sizestring默认 1:1

图像生成的比例

支持以下比例,也可传入 auto 由服务端自动选择合适比例:

size 类型
auto 自动
1:1 正方
3:2 横图
2:3 竖图
4:3 横图
3:4 竖图
5:4 横图
4:5 竖图
16:9 横图
9:16 竖图
2:1 横图
1:2 竖图
3:1 横图
1:3 竖图
21:9 横图
9:21 竖图

也支持直接传入像素尺寸,例如 1881x836 / 887x1774。

当 size 传入 auto 时,默认比例为 1:1。

resolutionstring默认 1k

输出分辨率档位

可选值:1k / 2k / 4k

size × resolution → 实际像素对应关系:

size 1k 2k 4k
1:1 1024×1024 / 1254×1254 2048×2048 2880×2880
3:2 1536×1024 2048×1360 3520×2336
2:3 1024×1536 1360×2048 2336×3520
4:3 1024×768 2048×1536 3312×2480
3:4 768×1024 1536×2048 2480×3312
5:4 1280×1024 / 1448×1086 2560×2048 3216×2576
4:5 1024×1280 / 1122×1402 2048×2560 2576×3216
16:9 1536×864 / 1672×941 2048×1152 3840×2160
9:16 864×1536 / 941×1672 1152×2048 2160×3840
2:1 2048×1024 / 1774×887 2688×1344 3840×1920
1:2 1024×2048 / 887×1774 1344×2688 1920×3840
3:1 1881×836 / 1536×512 3072×1024 3840×1280
1:3 887×1774 / 512×1536 1024×3072 1280×3840
21:9 2016×864 / 1915×821 2688×1152 3840×1648
9:21 864×2016 / 821×1915 1152×2688 1648×3840

4K 支持上述 15 个比例;也可以直接通过 size 传入表格中的像素尺寸。

image_urlsarray

参考图数组(OpenAI 标准字段),传入后走图生图模式

其它 OpenAI 标准字段(response_format、style)不支持,会被忽略。任务结果只返回 url——如需 base64 请自行下载转换。

official_fallbackboolean默认 false

是否使用官方渠道兜底

  • false:不使用(默认)
  • true:使用官方渠道

使用场景示例

文生图(最简请求)

{
  "model": "gpt-image-2",
  "prompt": "一只橘猫坐在窗台上看夕阳,水彩画风格"
}

文生图(指定比例 + 2K)

{
  "model": "gpt-image-2",
  "prompt": "a corgi astronaut on the moon, cinematic, 8k",
  "size": "16:9",
  "resolution": "2k"
}

文生图(4K 输出)

{
  "model": "gpt-image-2",
  "prompt": "星空下的古老城堡",
  "size": "16:9",
  "resolution": "4k"
}

文生图(多张)

{
  "model": "gpt-image-2",
  "prompt": "星空下的古老城堡",
  "size": "16:9",
  "resolution": "4k",
  "n": 2
}

图生图(参考图 = URL)

{
  "model": "gpt-image-2",
  "prompt": "把这张照片变成水彩画风格",
  "image_urls": [
    "https://example.com/photo.jpg"
  ]
}

图生图(参考图 = base64)

{
  "model": "gpt-image-2",
  "prompt": "把这张照片变成水彩画风格",
  "image_urls": [
    "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA..."
  ]
}

图生图(多参考图融合,URL + base64 混填)

{
  "model": "gpt-image-2",
  "prompt": "把这两张照片融合成一张海报",
  "size": "4:3",
  "resolution": "2k",
  "image_urls": [
    "https://example.com/photo-a.jpg",
    "data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA..."
  ]
}

Response

codeinteger

响应状态码

dataarray

返回数据数组

查询任务结果

提交成功后返回 task_id,通过 GET /v1/tasks/{task_id} 轮询任务状态,详见 任务查询接口。

成功响应示例

{
  "code": 200,
  "data": {
    "id": "task_01KPQ7J7DWB7QZ3WCEK3YVPBRA",
    "status": "completed",
    "progress": 100,
    "created": 1776748674,
    "completed": 1776748726,
    "actual_time": 52,
    "cost": 0.05279,
    "credits_cost": 0.5279,
    "estimated_time": 100,
    "result": {
      "images": [
        {
          "url": [
            "https://26j.cn/f/image/xxxxxxxx-gpt_image_2_task_xxx_0.png"
          ],
          "expires_at": 1776835126
        }
      ]
    }
  }
}

取图方式:data.result.images[0].url[0]

任务状态说明

状态 含义
submitted 已提交
processing 上游处理中
completed 成功,result.images 可用
failed 失败,查看 error.message

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