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Google/nano-banana-pro-edit
nano-banana-pro-edit
Precise image editing via Gemini 3.0 Pro API with native 4K output. Delivers reliable local modifications and high stability at an affordable cost-per-request. Built for free testing and stable API workflows.
Image to ImageMulti-Image
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Nano Banana Pro Edit Pricing
| Parameters | Price | Original Price | Discount |
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Examples
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Fast & Affordable Nano Banana Pro Edit API (Gemini 3.0 Pro Image Editing Integration)
Google Nano Banana Pro Edit API (powered by the Gemini 3.0 Pro Image model) delivers cost-effective, production-grade AI image editing for developers and creative teams. This premium Gemini image editing API integration helps you transform existing visuals into high-resolution outputs up to 4K through natural-language instructions. The Gemini model provides semantic reasoning for complex edits, while the API provides stable integration for scalable workflows on Flaq AI.
Key Features of Nano Banana Pro Edit API
- High-Fidelity Image Editing up to 4K: Produce crisp, production-ready 4K edited images with fine detail, realistic textures, and clean edges through Gemini image editing API integration.
- Context-Aware Semantic Image Editing: Edit images with natural-language prompts while preserving object relationships, lighting logic, and scene coherence using the Gemini 3.0 Pro Image model.
- Multilingual On-Image Typography Editing: Add, replace, and refine on-image text across multiple languages with improved font clarity and translation-aware rendering.
- Professional Camera-Style API Controls: Adjust lens perspective, focus, depth of field (bokeh), and color grading for advanced visual direction in API-based editing pipelines.
- Complete Aspect Ratio Flexibility: API supports 1:1, 4:3, 16:9, 21:9, and 9:16 outputs, suitable for ads, social media, product pages, and cinematic layouts.
- Consistent Character & Brand Rendering: Maintain identity consistency, brand elements, and visual style across multiple edited images.
How to Use Nano Banana Pro Edit API for Professional 4K Image Editing on Flaq AI
- Input: Existing image(s) (JPEG/PNG) plus natural-language editing prompts
- Output: High-resolution edited images up to 4K (JPEG/PNG) through Nano Banana Pro Edit API integration
- Aspect Ratios: 11 supported formats including 16:9, 9:16, 1:1, 3:2, 2:3, 4:3, 3:4, 4:5, 5:4, 21:9, and 9:21.
- Capabilities: Prompt-based editing, style transfer, smart relighting, background replacement, and object-level manipulation powered by the Gemini Pro Image model
Best Use Cases for Nano Banana Pro Edit API Integration
- Marketing & Branding: Rapidly localize and refresh campaign creatives with high-quality AI image editing API workflows.
- Product Photography Optimization: Update backgrounds, lighting, and composition for catalog-ready product visuals without full reshoots.
- Social Media Content Production: Generate high-volume image variants with consistent style and brand alignment for multi-platform publishing.
- Professional Design Iteration: Accelerate concept refinement with controlled, semantic image edits up to 4K for creative and design teams.
Note Please ensure your prompts comply with Google’s Safety Guidelines. If an error occurs, review your prompt for restricted content, adjust it, and try again.
Nano Banana Pro Edit vs Competitors: Comparative Analysis
- Nano Banana Pro Edit vs. FLUX.1 [dev]
FLUX.1 [dev] focuses on detail-heavy technical generation workflows. Nano Banana Pro Edit API emphasizes semantic, instruction-driven editing with layout-aware changes, making it stronger for practical production editing scenarios. - Nano Banana Pro Edit vs. GPT-Image-1 (OpenAI)
GPT-Image-1 is a broad creative image model with wide stylistic range. Nano Banana Pro Edit API is optimized for targeted edits, multilingual typography handling, and predictable output control for professional teams. - Nano Banana Pro Edit vs. Original Nano Banana
Original Nano Banana is optimized for rapid, lightweight iterations. Nano Banana Pro Edit prioritizes premium-quality editing with better reasoning, sharper text rendering, and stronger consistency across complex multi-step edits. - Nano Banana Pro Edit vs. Seedream
Seedream is strong for stylized, fast visual generation. Nano Banana Pro Edit is tuned for reliable typography, photorealistic editing, and controlled mixed-media composition in production pipelines. - Nano Banana Pro Edit vs. Qwen Image 2509
Qwen Image performs well in open-source and document-style contexts. Nano Banana Pro Edit API differentiates with high-fidelity editing quality up to 4K and robust multilingual design control for global content operations.
Use the Nano Banana Pro Edit Model Directly in Powerful AI Tools
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.
API Examples
Submit Example
// Step 1: Submit generation request
// width and height must be aspect-ratio integers such as 16 and 9,
// not pixel dimensions like 768 and 1280.
// Currently all width/height values are passed as ratio integers,
// and the backend does not support custom pixel dimensions for these fields.
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: 'nano-banana-pro-edit',
prompt: 'Transform this image into a watercolor painting style',
width: 16, // Aspect-ratio value, not pixel width
height: 9, // Aspect-ratio value, not pixel height
resolution: '2k', // Supported values: '1k', '2k', '4k'
image_url_list: [
'https://example.com/image1.jpg',
'https://example.com/image2.jpg'
]
})
});
const { data } = await response.json();
const taskId = data.task_id;
Polling Example
// 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));
}
Submit Example
# 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': 'nano-banana-pro-edit',
'prompt': 'Transform this image into a watercolor painting style',
'width': 16, # Aspect-ratio value, not pixel width
'height': 9, # Aspect-ratio value, not pixel height
'resolution': '2k', # Supported values: '1k', '2k', '4k'
'image_url_list': [
'https://example.com/image1.jpg',
'https://example.com/image2.jpg'
]
}
)
result = response.json()
task_id = result['data']['task_id']
Polling Example
# 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)
Submit Example
# 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": "nano-banana-pro-edit",
"prompt": "Transform this image into a watercolor painting style",
"width": 16,
"height": 9,
"resolution": "2k",
"image_url_list": [
"https://example.com/image1.jpg",
"https://example.com/image2.jpg"
]
}'
Polling Example
# 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"