
Text to Image
Create AI images from text prompts
High-quality image generation via Qwen Image 2.0 API with sharp text rendering and realistic visuals. Stable and affordable for high-volume production. Built for free testing and stable API workflows.
Try the AI Image Generator now
| Parameters | Price | Original Price | Discount |
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Qwen Image 2.0 API from Alibaba delivers high-quality, cost-effective AI image generation for developers and creative teams. This versatile text-to-image API integration enables you to produce professional visuals from natural-language descriptions per image. Built on Alibaba's latest multimodal architecture, the Qwen Image 2.0 model combines strong prompt comprehension with flexible resolution control, while the API provides reliable integration for scalable production workflows on Flaq AI.
Note Please ensure your prompts comply with Alibaba's content safety guidelines. If an error occurs, review your prompt for restricted content, adjust it, and try again.
Qwen Image 2.0 vs. Qwen Image 2.0 Pro Qwen Image 2.0 Pro offers enhanced detail fidelity and premium rendering quality for demanding commercial applications. Qwen Image 2.0 provides excellent quality at a lower price point, making it the preferred choice for high-volume workflows where cost-efficiency is a priority.
Qwen Image 2.0 vs. DALL-E 3 (OpenAI) DALL-E 3 offers broad creative versatility and strong English-language prompt understanding. Qwen Image 2.0 API differentiates through lower per-image costs, superior multilingual support (especially Chinese), and flexible custom resolution control—making it ideal for developers building localized or high-throughput applications.
Qwen Image 2.0 vs. Stable Diffusion XL Stable Diffusion XL provides open-source flexibility and extensive community fine-tuning options. Qwen Image 2.0 offers hassle-free API integration, better out-of-the-box prompt adherence, and no infrastructure management required—ideal for teams seeking affordable, production-ready image generation without operational overhead.
Qwen Image 2.0 vs. Midjourney v6 Midjourney v6 excels at artistic aesthetics and community-curated visual styles. Qwen Image 2.0 provides programmatic API access, predictable per-image pricing, flexible resolution control, and seamless integration into production workflows—making it superior for developers requiring scalable, cost-effective image generation.
Qwen Image 2.0 vs. Seedream 4.5 Seedream 4.5 specializes in stylized illustration and anime generation. Qwen Image 2.0 offers broader versatility across photorealistic and artistic styles, stronger multilingual text rendering, and more flexible resolution options through affordable Alibaba API integration.
Explore several AI creation tools for quick image and video workflows in your browser, then scale successful ideas with Flaq AI's production-ready model APIs. Flaq AI provides a unified API layer for all models, making it easy to use and scale your workflows.

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// Step 1: Submit generation request
const response = await fetch('https://api.flaq.ai/api/v1/image/task', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
},
body: JSON.stringify({
model_name: 'qwen-image-2.0',
prompt: 'A serene landscape with mountains and a lake at sunset',
width: 16,
height: 9
})
});
const { data } = await response.json();
const taskId = data.task_id;
// Step 2: Poll for results
const taskId = data.task_id;
const pollResult = async (taskId) => {
const res = await fetch(`https://api.flaq.ai/api/v1/image/${taskId}`, {
headers: { 'Authorization': 'Bearer YOUR_API_KEY' }
});
return res.json();
};
while (true) {
const pollResultData = await pollResult(taskId);
const status = pollResultData.data.task_status;
if (status === 'succeed') {
console.log(pollResultData.data.task_result.images[0].url);
break;
}
if (status === 'failed') {
console.error(pollResultData.data.task_status_msg);
break;
}
await new Promise(resolve => setTimeout(resolve, 10000));
}
# Step 1: Submit generation request
import requests
response = requests.post(
'https://api.flaq.ai/api/v1/image/task',
headers={
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
},
json={
'model_name': 'qwen-image-2.0',
'prompt': 'A serene landscape with mountains and a lake at sunset',
'width': 16,
'height': 9
}
)
result = response.json()
task_id = result['data']['task_id']
# Step 2: Poll for results
task_id = response.json()['data']['task_id']
poll_url = f"https://api.flaq.ai/api/v1/image/{task_id}"
while True:
poll_result = requests.get(poll_url, headers={'Authorization': 'Bearer YOUR_API_KEY'}).json()
status = poll_result['data']['task_status']
if status == 'succeed':
print(poll_result['data']['task_result']['images'][0]['url'])
break
if status == 'failed':
print(poll_result['data']['task_status_msg'])
break
time.sleep(10)
# Step 1: Submit generation request
curl -X POST https://api.flaq.ai/api/v1/image/task \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model_name": "qwen-image-2.0",
"prompt": "A serene landscape with mountains and a lake at sunset",
"width": 16,
"height": 9
}'
# Step 2: Poll for results
# Replace {task_id} with the task_id returned from the submit response
curl -X GET "https://api.flaq.ai/api/v1/image/{task_id}" \
-H "Authorization: Bearer YOUR_API_KEY"