Qwen Image 3.0 Pro

Qwen Image 3.0 Pro is Alibaba's flagship third-generation AI image generation model built on a Diffusion Transformer architecture. Engineered for high information density and professional production, it accepts ultra-long prompts of up to 4,500 tokens, allowing a single pass to generate complex layouts like newspaper front pages, multi-panel storyboards, academic papers, and detailed UI interfaces. It delivers micro-level detail and industry-leading typography, rendering legible small text down to 10px across 12 native languages and 20+ fonts.

Qwen Image 3.0 Pro

Base URL

https://api.icreat.ai

Authentication

All API requests must be authenticated with an API Key. You can obtain an API Key from the console.

export ICREAT_API_KEY="your-api-key-here"

HTTP Request Headers

import os

API_KEY = os.environ.get("ICREAT_API_KEY")
headers = {
    "Content-Type": "application/json",
    "Authorization": "Bearer " + API_KEY,
}

Protect your API Key

Never expose your API Key in client-side code or public repositories. Use environment variables or a backend proxy.

Code Examples

Image and video generation uses a three-step async flow: submit to get task_id, poll status, then fetch results when status is SUCCEEDED.

1. Submit Task

Send a generation request to the submit endpoint.

POST/v1/task/submit/aliyun/qwen-image-3-0-pro

curl --fail-with-body --connect-timeout 10 --max-time 60 \
  -X POST https://api.icreat.ai/v1/task/submit/aliyun/qwen-image-3-0-pro \
  -H "Authorization: Bearer ${ICREAT_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{
  "input": {
    "messages": [
      {
        "role": "user",
        "content": [
          {
            "image": "https://example.com/example.png"
          },
          {
            "text": "Replace the main character clothing with a cyberpunk-style glowing jacket, and adjust the background to a rainy night neon street district"
          }
        ]
      }
    ]
  },
  "parameters": {
    "watermark": true,
    "size": "1024*1024"
  }
}'

2. Poll Status

Poll with task_id. Response contains only status.

POST/v1/task/query-status

curl --connect-timeout 10 --max-time 60 \
  -X POST https://api.icreat.ai/v1/task/query-status \
  -H "Authorization: Bearer ${ICREAT_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{
  "task_id": "task-xxx"
}'

3. Get Result

Fetch output when the task succeeds.

POST/v1/task/get-result

curl --connect-timeout 10 --max-time 60 \
  -X POST https://api.icreat.ai/v1/task/get-result \
  -H "Authorization: Bearer ${ICREAT_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{
  "task_id": "task-xxx"
}'

Input Schema

Submit Task — Input

The following parameters are accepted in the submit request body.

Total: 2 Required: 1 Optional: 1

inputobjectrequired

Generation input payload.

parametersobject

Generation parameters.

Poll Status — Input

Total: 1 Required: 1 Optional: 0

task_idstringrequired

Task ID from the submit endpoint.

Get Result — Input

Total: 1 Required: 1 Optional: 0

task_idstringrequired

Task ID from the submit endpoint.

Output Schema

Submit Task — Output

Total: 1

task_idstring

Async task identifier.

Poll Status — Output

Total: 1

statusstring

Current task status. Fetch results when SUCCEEDED.

Get Result — Output

Top-level array of resource objects.

Total: 3

typestring

Resource type; Image for this model.

urlstring

Preview/access URL.

download_urlstring

Download URL.

LLM Prompt

The Markdown below is an LLM-friendly prompt you can paste into AI assistants (e.g. Cursor, ChatGPT) to help them understand this model's API, call flow, and key parameters. Use Copy for AI or copy from the code block below.

# aliyun/qwen-image-3-0-pro

> Qwen Image 3.0 Pro is Alibaba's flagship third-generation AI image generation model built on a Diffusion Transformer architecture.

## Overview

Use the iCreat three-step async task API: submit a generation request, poll status, then fetch the image URL on success.

## API Info

- **Base URL**：`https://api.icreat.ai`
- **Submit endpoint (POST)**：`/v1/task/submit/aliyun/qwen-image-3-0-pro`
- **Poll endpoint (POST)**：`/v1/task/query-status`
- **Get result endpoint (POST)**：`/v1/task/get-result`
- **Model ID**：`aliyun/qwen-image-3-0-pro`
- **Auth**：`Authorization: Bearer ${ICREAT_API_KEY}`

## Call Flow

1. **Submit**: POST submit path with body per Input Notes; response `{ "task_id": "..." }`
2. **Poll**: POST `/v1/task/query-status` with `{ "task_id": "..." }`; response contains **only** `{ "status": "SUBMITTED|SUCCEEDED|FAILED" }`
3. **Get result**: when `status` is `SUCCEEDED`, POST `/v1/task/get-result`; top-level array; read `url` or `download_url` when `type` is `Image`

### Input Notes

- Top-level body has sibling objects `input` and `parameters`
- `input.messages` (required, min 1): set `role` to `user`
- `input.messages[].content`: array of parts; use `text` for prompt/editing instruction, `image` for reference URL (I2I/edit)
- `parameters.size` (required): output dimensions, e.g. `"1024*1024"`
- `parameters.watermark` (optional): whether to add a watermark

### Output Notes

- Poll: read `status` only
- Result: top-level `[{ "type": "Image", "url": "...", "download_url": "..." }]`

## Notes

- Use the same `task_id` across all three steps; do not skip polling
- `FAILED` is terminal — check request parameters or reference media
- `input` and `parameters` are sibling top-level fields; do not nest them