Z.ai Image - QWave API

POST

tasks

Z.ai Image

curl --request POST \
  --url https://www.qingbo.dev/v1/tasks \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "<string>",
  "action": "<string>",
  "prompt": "<string>",
  "n": 123,
  "aspect_ratio": "<string>",
  "resolution": "<string>",
  "callback_url": "<string>",
  "callback_events": [
    "<string>"
  ],
  "prompt_extend": true
}
'

import requests

url = "https://www.qingbo.dev/v1/tasks"

payload = {
    "model": "<string>",
    "action": "<string>",
    "prompt": "<string>",
    "n": 123,
    "aspect_ratio": "<string>",
    "resolution": "<string>",
    "callback_url": "<string>",
    "callback_events": ["<string>"],
    "prompt_extend": True
}
headers = {"Content-Type": "application/json"}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    model: '<string>',
    action: '<string>',
    prompt: '<string>',
    n: 123,
    aspect_ratio: '<string>',
    resolution: '<string>',
    callback_url: '<string>',
    callback_events: ['<string>'],
    prompt_extend: true
  })
};

fetch('https://www.qingbo.dev/v1/tasks', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://www.qingbo.dev/v1/tasks"

	payload := strings.NewReader("{\n  \"model\": \"<string>\",\n  \"action\": \"<string>\",\n  \"prompt\": \"<string>\",\n  \"n\": 123,\n  \"aspect_ratio\": \"<string>\",\n  \"resolution\": \"<string>\",\n  \"callback_url\": \"<string>\",\n  \"callback_events\": [\n    \"<string>\"\n  ],\n  \"prompt_extend\": true\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://www.qingbo.dev/v1/tasks")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"<string>\",\n  \"action\": \"<string>\",\n  \"prompt\": \"<string>\",\n  \"n\": 123,\n  \"aspect_ratio\": \"<string>\",\n  \"resolution\": \"<string>\",\n  \"callback_url\": \"<string>\",\n  \"callback_events\": [\n    \"<string>\"\n  ],\n  \"prompt_extend\": true\n}")
  .asString();

{
  "task_id": "task-wave1775285160b950328499",
  "model": "z-image-turbo",
  "action": "generate",
  "status": "queued",
  "created_at": 1775285160040,
  "progress": 0
}

智谱 Z.ai 推出的轻量快速图像生成模型,中英双语 Prompt 均良好支持,延迟低、单价低,适合批量草图、运营素材、快速预览等高频场景。按张计费,纯文生图(不接受参考图),固定单次返回 1 张。

定价

模型	单价(每张)
`z-image-turbo`	`$0.01125`

调用示例

curl -X POST https://www.qingbo.dev/v1/tasks \
  -H "Authorization: Bearer $WAVE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "z-image-turbo",
    "prompt": "夕阳下的海边咖啡馆,木质露台,暖色调",
    "aspect_ratio": "16:9",
    "resolution": "1K"
  }'

curl -X POST https://www.qingbo.dev/v1/tasks \
  -H "Authorization: Bearer $WAVE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "z-image-turbo",
    "prompt": "一只柴犬",
    "prompt_extend": true,
    "aspect_ratio": "1:1",
    "resolution": "2K"
  }'

{
  "task_id": "task-wave1775285160b950328499",
  "model": "z-image-turbo",
  "action": "generate",
  "status": "queued",
  "created_at": 1775285160040,
  "progress": 0
}

提交后用 GET /v1/tasks/{task_id} 轮询状态,详见任务系统。

可用模型

模型 ID	说明
`z-image-turbo`	轻量快速,中英双语,1K/2K,纯文生(无参考图)

通用参数

model

string

必填

从可用模型列表中选一个

action

string

默认值:"generate"

操作类型,z-image-turbo 仅支持 generate(文生图)

prompt

string

必填

图像描述文本,中英文均良好支持。最长 800 字符

integer

默认值:"1"

生成数量。该模型固定单次返回 1 张,不支持 n > 1

aspect_ratio

string

默认值:"1:1"

画面宽高比,可选值:

1:1 — 正方形
4:3 / 3:4 — 横/竖版标准
16:9 / 9:16 — 横/竖版宽屏
3:2 / 2:3 — 横/竖版相机比

resolution

string

默认值:"1K"

输出分辨率,可选 1K / 2K

callback_url

string

Webhook 回调地址,任务终态时调用。详见回调机制

callback_events

string[]

指定要回调的事件,默认仅终态事件。详见回调机制

模型特定参数

prompt_extend

boolean

默认值:"false"

智能改写提示词。开启后 AI 自动优化提示词,效果更好但费用增加

注意事项

单次只能 1 张 — n 字段固定为 1,如需多张请多次提交任务
Prompt 上限 800 字符 — 超长 Prompt 请自行裁剪
prompt_extend 开启后费用上升 — AI 改写会消耗额外推理成本,批量场景请按需开启
纯文生图 — 不接受 image_urls 参考图,如需图生图请选择其他模型

资源限制

项目	限制
单次生成数量	固定 1 张
Prompt 长度	≤ 800 字符
输出分辨率	`1K` / `2K`
输出文件	JPG,链接 24 小时有效

相关文档

任务系统详解 — 任务状态机 / 轮询节奏 / 异步推送
请求响应格式 — 通用错误码 / Headers / 限流
认证 — API Key 申请与使用

FLUX 系列Black Forest Labs FLUX — Kontext 图像编辑(FLUX.1 Kontext)与 FLUX.2 文生图

Z.ai Image

curl --request POST \
  --url https://www.qingbo.dev/v1/tasks \
  --header 'Content-Type: application/json' \
  --data '
{
  "model": "<string>",
  "action": "<string>",
  "prompt": "<string>",
  "n": 123,
  "aspect_ratio": "<string>",
  "resolution": "<string>",
  "callback_url": "<string>",
  "callback_events": [
    "<string>"
  ],
  "prompt_extend": true
}
'

import requests

url = "https://www.qingbo.dev/v1/tasks"

payload = {
    "model": "<string>",
    "action": "<string>",
    "prompt": "<string>",
    "n": 123,
    "aspect_ratio": "<string>",
    "resolution": "<string>",
    "callback_url": "<string>",
    "callback_events": ["<string>"],
    "prompt_extend": True
}
headers = {"Content-Type": "application/json"}

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

print(response.text)

const options = {
  method: 'POST',
  headers: {'Content-Type': 'application/json'},
  body: JSON.stringify({
    model: '<string>',
    action: '<string>',
    prompt: '<string>',
    n: 123,
    aspect_ratio: '<string>',
    resolution: '<string>',
    callback_url: '<string>',
    callback_events: ['<string>'],
    prompt_extend: true
  })
};

fetch('https://www.qingbo.dev/v1/tasks', options)
  .then(res => res.json())
  .then(res => console.log(res))
  .catch(err => console.error(err));

package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://www.qingbo.dev/v1/tasks"

	payload := strings.NewReader("{\n  \"model\": \"<string>\",\n  \"action\": \"<string>\",\n  \"prompt\": \"<string>\",\n  \"n\": 123,\n  \"aspect_ratio\": \"<string>\",\n  \"resolution\": \"<string>\",\n  \"callback_url\": \"<string>\",\n  \"callback_events\": [\n    \"<string>\"\n  ],\n  \"prompt_extend\": true\n}")

	req, _ := http.NewRequest("POST", url, payload)

	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(string(body))

}

HttpResponse<String> response = Unirest.post("https://www.qingbo.dev/v1/tasks")
  .header("Content-Type", "application/json")
  .body("{\n  \"model\": \"<string>\",\n  \"action\": \"<string>\",\n  \"prompt\": \"<string>\",\n  \"n\": 123,\n  \"aspect_ratio\": \"<string>\",\n  \"resolution\": \"<string>\",\n  \"callback_url\": \"<string>\",\n  \"callback_events\": [\n    \"<string>\"\n  ],\n  \"prompt_extend\": true\n}")
  .asString();

{
  "task_id": "task-wave1775285160b950328499",
  "model": "z-image-turbo",
  "action": "generate",
  "status": "queued",
  "created_at": 1775285160040,
  "progress": 0
}

​定价

​调用示例

​可用模型

​通用参数

​模型特定参数

​注意事项

​资源限制

​相关文档

定价

调用示例

可用模型

通用参数

模型特定参数

注意事项

资源限制

相关文档