Gemini 3 Pro Image Preview (Nano Banana Pro)

gemini-3-pro-image-preview
byGoogle|Created Nov 20, 2025
Chat Completions

Gemini 3 Pro Image Preview (Nano Banana Pro) is Google’s most advanced image generation and editing model, built on Gemini 3 Pro. Building on the original Nano Banana, it offers much improved multimodal reasoning, real-world grounding, and high-fidelity visual synthesis. The model produces context-rich visuals—from infographics and diagrams to cinematic composites—and can incorporate up-to-the-minute information through Search grounding. It leads the industry with sophisticated text rendering in images, handles consistent multi-image blending, and maintains accurate identity preservation for up to five subjects. Nano Banana Pro gives users fine-grained creative controls like localized edits, lighting and focus adjustments, camera transformations, 2K/4K output, and flexible aspect ratios. Tailored for professional design, product visualization, storyboarding, and complex compositions, it remains efficient for everyday image creation needs.

Pricing

Pay-as-you-go rates for this model. More details can be found here.

Input Tokens (1M)

$1.00

Output Tokens (1M)

$6.00

Capabilities

Input Modalities

Text
Image
Audio
File

Output Modalities

Text
Image

Supported Parameters

Available parameters for API requests

Image Config
Max Completion Tokens
Reasoning Effort
Response Format
Stop
Temperature
Tool Choice
Tools
Top P
Web Search Options

Usage Analytics

Token usage of this model on our platform

Throughput

Time-To-First-Token (TTFT)

Code Example

Example code for using this model through our API with Python (OpenAI SDK) or cURL. Replace placeholders with your API key and model ID.

Basic request example. Ensure API key permissions. For more details, see our documentation.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.naga.ac/v1",
    api_key="YOUR_API_KEY",
)

resp = client.chat.completions.create(
    model="gemini-3-pro-image-preview",
    messages=[
        {{"role": "user", "content": "What's 2+2?"}}
    ],
    temperature=0.2,
)
print(resp.choices[0].message.content)