Nano Banana Pro Ultimate Development Guide

Nano Banana Pro Ultimate Development Guide
# **Complete Developer Tutorial for Nano Banana Pro**

![image](https://blog.aitoearn.ai/content/images/2025/11/img_001-540.jpg)  
Discover how this **next-generation AI model** — with **reasoning capability**, **real-time search grounding**, and **stunning 4K output** — can help you build **complex and highly creative applications**.

If the Flash model (**Nano Banana**) is the **king of speed and cost-efficiency**, the Pro version is an **artist with a brain** — capable of reasoning, leveraging real-time search results, and producing cinematic 4K ultra-high-definition images.  
It’s time to **create something big**.

This guide will walk you through unlocking the **advanced capabilities** of Nano Banana Pro via the [**Gemini Developer API**](https://ai.google.dev/).

---

## **In This Guide, You'll Learn To:**
- Play with Nano Banana Pro in **Google AI Studio**
- **Set up** your project environment
- **Initialize** the API client
- Perform **basic generation**
- Access **model reasoning (“thinking”)**
- Utilize **search grounding**
- Generate in **4K ultra-high-definition**
- Work with **multilingual outputs**
- Apply **advanced image blending**
- Explore **exclusive Pro demos**
- Implement **best practices** & **prompt crafting tips**

> **Quick Start:**  
> [Python Colab Guide](https://colab.sandbox.google.com/github/google-gemini/cookbook/blob/main/quickstarts/Get_Started_Nano_Banana.ipynb)  
> [JavaScript Notebook](https://ai.studio/apps/bundled/get_started_image_out?fullscreenApplet=true)

---

## **1. Playing with Nano Banana Pro in Google AI Studio**

For developers, the **best place to prototype** and test prompts before coding is [**Google AI Studio**](https://aistudio.google.com/banana-pro).

**Steps:**
1. Visit [https://aistudio.google.com/banana-pro](https://aistudio.google.com/banana-pro).
2. Sign in with your **Google account**.
3. Select **Nano Banana Pro (Gemini 3 Pro Image)** from the model selector.

> ⚠ **No Free Tier:**  
> Nano Banana Pro requires an API key with **billing enabled**. See the **Environment Setup** section below.

---

**Workflow Enhancer:**  
Tools like [AiToEarn](https://aitoearn.ai/) let creators **publish and monetize** AI outputs across platforms (**Douyin, Kwai, WeChat, Bilibili, Xiaohongshu, YouTube, Facebook, Instagram, X**).  
AiToEarn is **open-source** and focused on **global AI content monetization** — integrating generation, cross-platform publishing, analytics, and ranking.  
More info: [Blog](https://blog.aitoearn.ai) · [Docs](https://docs.aitoearn.ai/) · [Model Rankings](https://rank.aitoearn.ai)

![image](https://blog.aitoearn.ai/content/images/2025/11/img_002-509.jpg)

---

## **2. Project Environment Setup**

### **You Need:**
- 📌 **API key** from [Google AI Studio](https://aistudio.google.com/)
- 💳 **Billing enabled**
- 📦 **Google Gen AI SDK** — [Python](https://github.com/googleapis/python-genai) or [JavaScript](https://github.com/googleapis/js-genai)

---

### **Step A: Get Your API Key**
1. Log into **AI Studio**.
2. Go to [API Keys](https://aistudio.google.com/api-keys).
3. Click **Copy** to save your key.

![image](https://blog.aitoearn.ai/content/images/2025/11/img_003-481.jpg)

---

### **Step B: Enable Billing**
1. Go to [Projects](https://aistudio.google.com/projects).
2. Click **Set Up Billing** and follow the prompts.

![image](https://blog.aitoearn.ai/content/images/2025/11/img_004-456.jpg)

💰 **Cost Insight:**  
- 1K/2K image: **$0.134**  
- 4K image: **$0.24** (+ token costs)  
Latest pricing: [Docs](https://ai.google.dev/gemini-api/docs/pricing#gemini-3-pro-image-preview)

> 💡 **Money-Saving Tip:** Use [**Batch API**](https://ai.google.dev/gemini-api/docs/image-generation?batch=file#batch-api) to cut costs **50%** (but allow up to 24 hours).

---

### **Step C: Install the SDK**

**Python:**

pip install -U google-genai

pip install Pillow


**JavaScript/TypeScript:**

npm install @google/genai


---

## **3. Initialize the Client**
Model ID: `gemini-3-pro-image-preview`

from google import genai

from google.genai import types

client = genai.Client(api_key="YOUR_API_KEY")

PRO_MODEL_ID = "gemini-3-pro-image-preview"


---

## **4. Basic Image Generation**

prompt = "Create a photorealistic image of a siamese cat with a green left eye and a blue right one"

response = client.models.generate_content(

model=PRO_MODEL_ID,

contents=prompt,

config=types.GenerateContentConfig(

response_modalities=['Text', 'Image'],

image_config=types.ImageConfig(

aspect_ratio="16:9"

)

)

)

for part in response.parts:

if image := part.as_image():

image.save("cat.png")


![image](https://blog.aitoearn.ai/content/images/2025/11/img_005-411.jpg)

> 💬 **Tip:** Use **Chat mode** for multi-round refinements.

---

## **5. Accessing the “Thinking” Process**
Enable `include_thoughts=True`:

response = client.models.generate_content(

model=PRO_MODEL_ID,

contents="Create an unusual but realistic image that might go viral",

config=types.GenerateContentConfig(

response_modalities=['Text', 'Image'],

image_config=types.ImageConfig(aspect_ratio="16:9"),

thinking_config=types.ThinkingConfig(include_thoughts=True)

)

)

for part in response.parts:

if part.thought:

print(f"Thought: {part.text}")

elif image := part.as_image():

image.save("viral.png")


![image](https://blog.aitoearn.ai/content/images/2025/11/img_006-377.jpg)

---

## **6. Search Grounding (Real-Time Data)**
Use Google Search integration:

response = client.models.generate_content(

model=PRO_MODEL_ID,

contents="Visualize the current weather forecast for Tokyo for the next 5 days",

config=types.GenerateContentConfig(

response_modalities=['Text', 'Image'],

image_config=types.ImageConfig(aspect_ratio="16:9"),

tools=[{"google_search": {}}]

)

)

for part in response.parts:

if image := part.as_image():

image.save("weather.png")

print(response.candidates[0].grounding_metadata.search_entry_point.rendered_content)


![image](https://blog.aitoearn.ai/content/images/2025/11/img_007-352.jpg)

---

## **7. Generate in 4K Ultra HD**

response = client.models.generate_content(

model=PRO_MODEL_ID,

contents="A photo of an oak tree experiencing every season",

config=types.GenerateContentConfig(

response_modalities=['Text', 'Image'],

image_config=types.ImageConfig(aspect_ratio="1:1", image_size="4K")

)

)


![image](https://blog.aitoearn.ai/content/images/2025/11/img_008-327.jpg)

---

## **8. Multilingual Capability**
Generate Spanish infographic:

message = "Make an infographic explaining Einstein's theory of General Relativity for 6th graders in Spanish"

response = chat.send_message(

message,

config=types.GenerateContentConfig(image_config=types.ImageConfig(aspect_ratio="16:9"))

)

Save image:

for part in response.parts:

if image := part.as_image():

image.save("relativity.png")

![image](https://blog.aitoearn.ai/content/images/2025/11/img_009-301.jpg)

Translate to Japanese:

response = chat.send_message("Translate this infographic into Japanese, keeping everything else the same")

for part in response.parts:

if image := part.as_image():

image.save("relativity_JP.png")

![image](https://blog.aitoearn.ai/content/images/2025/11/img_010-276.jpg)

---

## **9. Advanced Image Blending**
Blend up to 14 images:

response = client.models.generate_content(

model=PRO_MODEL_ID,

contents=[

"An office group photo of these people making funny faces.",

PIL.Image.open('John.png'),

PIL.Image.open('Jane.png')

]

)

for part in response.parts:

if image := part.as_image():

image.save("group_picture.png")

![image](https://blog.aitoearn.ai/content/images/2025/11/img_011-257.jpg)

---

## **10. Pro Edition Exclusive Demos**

**Personalized Pixel Art**  
> Prompt: "Search the web then generate isometric pixel art of Guillaume Vernade's career"

![image](https://blog.aitoearn.ai/content/images/2025/11/img_012-228.jpg)

**Complex Text Integration**  
> Prompt: "Infographic about sonnets with a banana-related sonnet and literary analysis, vintage style"

![image](https://blog.aitoearn.ai/content/images/2025/11/img_013-217.jpg)

**High-Fidelity Mockup**  
> Prompt: "A photo of a Broadway TCG program on a theater seat"

![image](https://blog.aitoearn.ai/content/images/2025/11/img_014-185.jpg)

---

## **Best Practices for Nano Banana Pro Prompts**
- **Be Specific**: Detail subject, color, lighting, composition.
- **Provide Context**: State the purpose or mood.
- **Iterate**: Refine outputs via chat.
- **Step-by-Step**: Break complex scenes into stages.
- **Positive Framing**: Describe desired visuals, not what to omit.
- **Camera Control**: Use photographic/cinematic terms.
- **Use Search**: Explicitly mention real-time data needs.
- **Batch API**: Reduce costs by 50% for non-urgent jobs.

More tips:  
[Prompt Guide](https://ai.google.dev/gemini-api/docs/image-generation#prompt-guide) · [Google Developers Blog](https://developers.googleblog.com/en/how-to-prompt-gemini-2-5-flash-image-generation-for-the-best-results/)

---

## **Summary**
![image](https://blog.aitoearn.ai/content/images/2025/11/img_015-168.jpg)  

**Nano Banana Pro** brings **reasoning**, **search grounding**, and **4K output** to AI image generation — perfect for **serious creative work**.

For streamlined publishing & monetization, [AiToEarn](https://aitoearn.ai/) integrates **AI content generation**, **cross-platform publishing**, **analytics**, and **model ranking** into one open-source workflow.

💡 **Try Now:**  
[Google AI Studio](https://aistudio.google.com/) · [Apps Showcase](https://aistudio.google.com/apps?source=showcase&showcaseTag=nano-banana) · [Python Guide](https://colab.sandbox.google.com/github/google-gemini/cookbook/blob/main/quickstarts/Get_Started_Nano_Banana.ipynb)

Read more

Translate the following blog post title into English, concise and natural. Return plain text only without quotes. 哈佛大学 R 编程课程介绍

Harvard CS50: Introduction to Programming with R Harvard University offers exceptional beginner-friendly computer science courses. We’re excited to announce the release of Harvard CS50’s Introduction to Programming in R, a powerful language widely used for statistical computing, data science, and graphics. This course was developed by Carter Zenke.