google/gemini-3-pro-image-preview
65,536 context · $2.00/M input tokens · $12.00/M output tokens
Nano Banana Pro is Google’s most advanced image-generation and editing model, built on Gemini 3 Pro. It extends the original Nano Banana with significantly improved multimodal reasoning, real-world grounding, and...
Pricing
Pay-per-use
No upfront costs, pay only for what you use
API Usage
Use the following code examples to integrate with our API:
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="google/gemini-3-pro-image-preview",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)Model Introduction
Google gemini-3-pro-image-preview
google gemini-3-pro-image-preview
Why It Looks Great
- Large Language Model architecture for efficient processing
- 65536 context window for long document handling
- Competitive pricing at $2.2/$13.2 per million tokens
Key Features
- Context Window: 65536 tokens
- Max Output: 32768 tokens
- Vision: Supported
- Function Calling: Supported
Specifications
| Specification | Value |
|---|---|
| Provider | |
| Model Type | Large Language Model (LLM) |
| Architecture | N/A |
| Context Window | 65536 tokens |
| Max Output | 32768 tokens |
| Input | Text |
| Output | Text |
| Vision | Supported |
| Function Calling | Supported |
Pricing
| Token Type | Cost per Million Tokens |
|---|---|
| Input | $2.2 |
| Output | $13.2 |
How to Use
- Write your prompt — describe the task, provide context, and specify desired output format.
- Submit — the model processes your request and returns the response.
API Integration
Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: google/gemini-3-pro-image-preview
API Usage
Python SDK
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://llm.wavespeed.ai/v1"
)
response = client.chat.completions.create(
model="google/gemini-3-pro-image-preview",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)cURL
curl https://llm.wavespeed.ai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "google/gemini-3-pro-image-preview",
"messages": [{"role": "user", "content": "Hello!"}]
}'Notes
- Model: google/gemini-3-pro-image-preview
- Provider: Google
Info
Supported Functionality
API Access Guide
Gemini 3 Pro Image Preview API
google/gemini-3-pro-image-preview
Nano Banana Pro is Google’s most advanced image-generation and editing model, built on Gemini 3 Pro. It extends the original Nano Banana with significantly improved multimodal reasoning, real-world grounding, and...
Input
$2 /M
Output
$12 /M
Context
66K
Max Output
33K
Vision
Supported
Try Gemini 3 Pro Image Preview on WaveSpeedAI
Access Gemini 3 Pro Image Preview through our unified API — OpenAI-compatible, no cold starts, transparent pricing.
Open PlaygroundFrequently Asked Questions about Gemini 3 Pro Image Preview
How much does Gemini 3 Pro Image Preview cost via the API?+
Pricing on WaveSpeedAI: $2.00 per million input tokens and $12.00 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.
What is the context window of Gemini 3 Pro Image Preview?+
Gemini 3 Pro Image Preview supports up to 66K tokens of context with up to 33K tokens of output per request.
Is Gemini 3 Pro Image Preview OpenAI-compatible?+
Yes. WaveSpeedAI exposes Gemini 3 Pro Image Preview through an OpenAI-compatible endpoint at https://llm.wavespeed.ai/v1. Point the official OpenAI SDK at this base URL with your WaveSpeedAI API key — no other code changes required.
How do I get started with Gemini 3 Pro Image Preview?+
Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with model id set to the value shown above. New accounts receive free credits to evaluate Gemini 3 Pro Image Preview before paying per token.