curl --request POST \
--url https://xcompute.us/v1/images/generations \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'Content-Type: application/json' \
--data '{
"model": "gpt-image-2.5-async",
"prompt": "未来城市夜景,电影感灯光,无文字",
"size": "1536x1024",
"quality": "medium"
}'
import requests
response = requests.post(
"https://xcompute.us/v1/images/generations",
headers={
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json",
},
json={
"model": "gpt-image-2.5-async",
"prompt": "未来城市夜景,电影感灯光,无文字",
"size": "1536x1024",
"quality": "medium",
},
timeout=30,
)
response.raise_for_status()
print(response.json()["id"])
{
"id": "task_AVzfphDDvLn189o8FyF07uEzx1skzfJP",
"status": "queued",
"mode": "generate",
"model": "gpt-image-2.5-async",
"size": "1536x1024",
"quality": "medium",
"created_at": "2026-09-11 03:33:10"
}
图像生成
GPT Image 2.5 异步图像生成
提交 GPT Image 2.5 异步任务并轮询获取图片。
POST
https://xcompute.us
/
v1
/
images
/
generations
curl --request POST \
--url https://xcompute.us/v1/images/generations \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'Content-Type: application/json' \
--data '{
"model": "gpt-image-2.5-async",
"prompt": "未来城市夜景,电影感灯光,无文字",
"size": "1536x1024",
"quality": "medium"
}'
import requests
response = requests.post(
"https://xcompute.us/v1/images/generations",
headers={
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json",
},
json={
"model": "gpt-image-2.5-async",
"prompt": "未来城市夜景,电影感灯光,无文字",
"size": "1536x1024",
"quality": "medium",
},
timeout=30,
)
response.raise_for_status()
print(response.json()["id"])
{
"id": "task_AVzfphDDvLn189o8FyF07uEzx1skzfJP",
"status": "queued",
"mode": "generate",
"model": "gpt-image-2.5-async",
"size": "1536x1024",
"quality": "medium",
"created_at": "2026-09-11 03:33:10"
}
使用
保存响应中的
优先读取顶层
gpt-image-2.5-async 提交异步生成任务。提交接口与同步生成相同,通过模型名区分调用方式;成功提交后立即返回任务 ID。
提交任务
curl --request POST \
--url https://xcompute.us/v1/images/generations \
--header 'Authorization: Bearer YOUR_API_KEY' \
--header 'Content-Type: application/json' \
--data '{
"model": "gpt-image-2.5-async",
"prompt": "未来城市夜景,电影感灯光,无文字",
"size": "1536x1024",
"quality": "medium"
}'
import requests
response = requests.post(
"https://xcompute.us/v1/images/generations",
headers={
"Authorization": "Bearer YOUR_API_KEY",
"Content-Type": "application/json",
},
json={
"model": "gpt-image-2.5-async",
"prompt": "未来城市夜景,电影感灯光,无文字",
"size": "1536x1024",
"quality": "medium",
},
timeout=30,
)
response.raise_for_status()
print(response.json()["id"])
{
"id": "task_AVzfphDDvLn189o8FyF07uEzx1skzfJP",
"status": "queued",
"mode": "generate",
"model": "gpt-image-2.5-async",
"size": "1536x1024",
"quality": "medium",
"created_at": "2026-09-11 03:33:10"
}
id,后续用于查询任务结果。
查询任务
使用任务 ID 调用GET /v1/tasks/{task_id}:
cURL
curl --request GET \
--url https://xcompute.us/v1/tasks/task_AVzfphDDvLn189o8FyF07uEzx1skzfJP \
--header 'Authorization: Bearer YOUR_API_KEY'
{
"status": "completed",
"task_id": "task_AVzfphDDvLn189o8FyF07uEzx1skzfJP",
"progress": "100%",
"result_url": "https://example.com/generated-image.png",
"result": {
"items": [
{
"id": "task_AVzfphDDvLn189o8FyF07uEzx1skzfJP",
"status": "success",
"data": [
{
"url": "https://example.com/generated-image.png"
}
]
}
]
}
}
result_url。如果该字段为空,可以读取 result.items[0].data[0].url。
支持尺寸
异步调用的size 仅支持以下值:
| 档位 | 支持的 size |
|---|---|
| 标准 | 1024x1024、1536x1024、1024x1536、1024x1365、1365x1024、1088x1920、1920x1088 |
| 高分辨率 | 2048x2048、1712x2560、2560x1712、2048x1536、1152x2048、2048x1152、2880x2880、2560x3840、3840x2560、3840x2880、2160x3840、3840x2160 |
状态说明
顶层 status | 含义 | 处理方式 |
|---|---|---|
queued | 任务已进入队列 | 继续轮询 |
in_progress | 任务正在执行 | 继续轮询 |
completed | 任务执行完成 | 读取 result_url |
failed | 任务执行失败 | 读取 error 或结果项中的 error |
cancelled | 任务已取消 | 停止轮询 |
接入建议
- 每 3 到 5 秒查询一次,最长等待 10 分钟。
- 停止轮询不会取消服务端任务。
- 不要调用
/v1/images/generations/async或/api/image-tasks/generations,它们不是当前客户接口。 - 异步调用使用
gpt-image-2.5-async。