Imagen 4.0

POST

tasks

Imagen 4.0

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

import requests

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

payload = {
    "model": "<string>",
    "action": "<string>",
    "prompt": "<string>",
    "n": 123,
    "seed": 123,
    "aspect_ratio": "<string>",
    "resolution": "<string>",
    "callback_url": "<string>",
    "callback_events": ["<string>"]
}
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,
    seed: 123,
    aspect_ratio: '<string>',
    resolution: '<string>',
    callback_url: '<string>',
    callback_events: ['<string>']
  })
};

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  \"seed\": 123,\n  \"aspect_ratio\": \"<string>\",\n  \"resolution\": \"<string>\",\n  \"callback_url\": \"<string>\",\n  \"callback_events\": [\n    \"<string>\"\n  ]\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  \"seed\": 123,\n  \"aspect_ratio\": \"<string>\",\n  \"resolution\": \"<string>\",\n  \"callback_url\": \"<string>\",\n  \"callback_events\": [\n    \"<string>\"\n  ]\n}")
  .asString();

{
  "task_id": "task-wave1775285160b950328499",
  "model": "imagen-4.0",
  "action": "generate",
  "status": "queued",
  "created_at": 1775285160040,
  "progress": 0
}

Imagen 4.0 from Google DeepMind — native 2K output, photorealistic lighting and materials, with high accuracy for Chinese and English text rendering. Suited for poster key visuals, marketing hero images, and artistic illustrations where image quality and text rendering matter. Per-image pricing, unified 2K output.

Pricing

Model	Price (per image)
`imagen-4.0`	`$0.0425`

Examples

curl -X POST https://www.qingbo.dev/v1/tasks \
  -H "Authorization: Bearer $WAVE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "imagen-4.0",
    "prompt": "Sunrise on a mountaintop, sea of clouds rolling, distant snow peaks glowing gold, photorealistic photography style"
  }'

curl -X POST https://www.qingbo.dev/v1/tasks \
  -H "Authorization: Bearer $WAVE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "imagen-4.0",
    "prompt": "Movie poster, large title \"STARFALL\", subtitle \"Coming 2026\", starry sky background, minimal whitespace",
    "aspect_ratio": "9:16",
    "n": 2
  }'

curl -X POST https://www.qingbo.dev/v1/tasks \
  -H "Authorization: Bearer $WAVE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "imagen-4.0",
    "prompt": "Modern minimalist office, morning light through floor-to-ceiling windows, green plant accents, magazine photography style",
    "aspect_ratio": "16:9",
    "seed": 42
  }'

{
  "task_id": "task-wave1775285160b950328499",
  "model": "imagen-4.0",
  "action": "generate",
  "status": "queued",
  "created_at": 1775285160040,
  "progress": 0
}

After submission, poll status with GET /v1/tasks/{task_id}. See Task System for details.

Available Models

Model ID	Description
`imagen-4.0`	Google DeepMind flagship text-to-image, native 2K, photorealistic, accurate Chinese and English text

Common Parameters

string

required

Choose one from the Available Models list

string

default:"generate"

Operation type. Imagen 4.0 supports only:

generate — Text-to-image (default)

string

required

Image description. Supports Chinese and English. Imagen 4.0 excels at scene detail, lighting, and text rendering

integer

default:"1"

Number of images to generate (returned in a single call)

integer

default:"-1"

Random seed. -1 for random; a fixed value reproduces similar results

string

default:"1:1"

Aspect ratio. Options:

1:1 — Square
4:3 / 3:4 — Standard landscape / portrait
16:9 / 9:16 — Widescreen landscape / portrait

string

Output resolution. Imagen 4.0 defaults to native 2K with no resolution tiers — leave empty

string

Webhook callback URL, invoked when the task reaches a terminal state. See Callback Mechanism

string[]

Event types to receive callbacks for. Defaults to all terminal events

Resource Limits

Item	Limit
Supported action	`generate` only (text-to-image)
Output resolution	Native 2K (fixed, no tier selection)
Aspect ratio	`1:1` / `4:3` / `3:4` / `16:9` / `9:16` (5 options)
Output file	JPG, URL valid for 24 hours

Task System — Task state machine / polling cadence / async push
Request & Response — Common error codes / Headers / rate limits
Authentication — API Key application and usage

Imagen 4.0

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

import requests

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

payload = {
    "model": "<string>",
    "action": "<string>",
    "prompt": "<string>",
    "n": 123,
    "seed": 123,
    "aspect_ratio": "<string>",
    "resolution": "<string>",
    "callback_url": "<string>",
    "callback_events": ["<string>"]
}
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,
    seed: 123,
    aspect_ratio: '<string>',
    resolution: '<string>',
    callback_url: '<string>',
    callback_events: ['<string>']
  })
};

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  \"seed\": 123,\n  \"aspect_ratio\": \"<string>\",\n  \"resolution\": \"<string>\",\n  \"callback_url\": \"<string>\",\n  \"callback_events\": [\n    \"<string>\"\n  ]\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  \"seed\": 123,\n  \"aspect_ratio\": \"<string>\",\n  \"resolution\": \"<string>\",\n  \"callback_url\": \"<string>\",\n  \"callback_events\": [\n    \"<string>\"\n  ]\n}")
  .asString();

{
  "task_id": "task-wave1775285160b950328499",
  "model": "imagen-4.0",
  "action": "generate",
  "status": "queued",
  "created_at": 1775285160040,
  "progress": 0
}

Text Generation

Image Generation

Video Generation

Audio

Tools & Embeddings

Task Management

Pricing

Examples

Available Models

Common Parameters

Resource Limits

​Pricing

​Examples

​Available Models

​Common Parameters

​Resource Limits

​Related Docs

Pricing

Examples

Available Models

Common Parameters

Resource Limits

Related Docs