Generate and edit images with Flux Kontext Pro API by Black Forest Labs. Get semantic control, character consistency, and reliable quality.
Try the AI Image Generator now
Flux Kontext Pro API delivers cost-effective, production-grade AI image generation with advanced multi-image context understanding for developers. This affordable Flux API integration enables you to transform creative visions into reality through intuitive text-to-image and image-to-image generation. Built on cutting-edge context-aware technology, it combines deep semantic reasoning with flexible API integration for professional-grade output at $0.04 per image.
// 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: 'flux-kontext-pro',
prompt: 'A beautiful sunset over mountains',
image_url_list: ['https://example.com/image1.jpg'], // Optional: 1-5 reference images
width: 16,
height: 9
})
});
const { data } = await response.json();
const taskId = data.task_id;
Note Please ensure your prompts comply with content safety guidelines. If an error occurs, review your prompt for restricted content, adjust it, and try again.
Flux Kontext Pro vs. Flux Kontext Max While Flux Kontext Max emphasizes maximum quality and enhanced detail for premium workflows, Flux Kontext Pro focuses on cost-effective professional generation with excellent multi-image context understanding. At $0.04 per image, it delivers outstanding results ideal for most production use cases.
Flux Kontext Pro vs. FLUX.1 [dev] FLUX.1 [dev] provides strong baseline generation capabilities. In contrast, Flux Kontext Pro enhances this foundation with advanced multi-image context processing, making it the superior choice for affordable, production-grade workflows requiring reference image integration.
Flux Kontext Pro vs. Google Nano Banana Pro Google Nano Banana Pro excels at semantic understanding, multilingual text rendering, and 4K output. Flux Kontext Pro distinguishes itself by focusing on multi-image context awareness and photorealistic generation, making it ideal for projects requiring multiple reference images through cost-effective API integration.
Flux Kontext Pro vs. Seedream Seedream excels at fast, stylized generation with strong anime and illustration aesthetics. Flux Kontext Pro is specifically tuned for photorealistic output, multi-image context processing, and professional mixed-media layouts with flexible aspect ratio support.
Flux Kontext Pro vs. Stable Diffusion XL Stable Diffusion XL is a strong contender in open-source ecosystems with broad style variety. Flux Kontext Pro distinguishes itself by focusing on advanced multi-image context understanding and sophisticated reference image processing for professional productions through production-grade API integration.
// Step 2: Poll for results
const taskId = data.task_id;
const pollResult = async (taskId) => {
const res = await fetch(`https://api.flaq.ai/api/v1/image/${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
import time
response = requests.post(
'https://api.flaq.ai/api/v1/image/task',
headers={
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
},
json={
'model_name': 'flux-kontext-pro',
'prompt': 'A beautiful sunset over mountains',
'image_url_list': ['https://example.com/image1.jpg'], # Optional: 1-5 reference images
'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": "flux-kontext-pro",
"prompt": "A beautiful sunset over mountains",
"image_url_list": ["https://example.com/image1.jpg"],
"width": 16,
"height": 9
}'
# Response: {"code":0,"data":{"task_id":"abc123","task_status":"submitted","response_url":"https://api.flaq.ai/api/v1/image/abc123"},"message":"success"}
# 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"