Using Gemini 3.1 Pro on Google AI Studio

Implementation guide · Gemini 3.1 · Google DeepMind

Serverless

Quick Start

1
Create an account at Google AI Studio and generate an API key.
2
Use the Google AI Studio SDK or REST API to call gemini-3.1-pro-preview — see the documentation for request format.
3
You'll be billed $1.25/1M input, $10.00/1M output tokens.

API Portal Documentation Model Card

Code Examples

Install

pip install google-genai

API key

GOOGLE_API_KEY

Model ID

gemini-3.1-pro-preview

Use the model name directly, e.g. "gemini-2.0-flash", "gemini-1.5-pro", or "gemini-2.5-pro-preview-05-06".

import os
from google import genai

client = genai.Client(api_key=os.environ["GOOGLE_API_KEY"])
response = client.models.generate_content(
    model="gemini-3.1-pro-preview",
    contents="Hello"
)
print(response.text)

About Google AI Studio

Google AI Studio is a model prototyping environment and API access point for Gemini models, offering an inference playground for developers to test and build AI applications.

View all models on Google AI Studio →

Pricing on Google AI Studio

Type	Price (per 1M)
Input tokens	$1.25
Output tokens	$10.00

Capabilities

VisionMultimodalReasoningFunction CallingTool UseStructured OutputsCode Execution

About Gemini 3.1 Pro

Google DeepMind's Gemini 3.1 Pro preview model (released Feb 19, 2026), refining Gemini 3 Pro with better thinking, improved token efficiency, enhanced factual consistency, and optimizations for software engineering and agentic workflows. Supports text, image, video, audio, and PDF inputs; text output only. 1M token input context window (65,536 output max). Knowledge cutoff: January 2025. Includes batch API, caching, code execution, function calling, search grounding, structured outputs, and thinking capabilities.

Full model details →

Model Specs

Released2026-02-19

Context1M

ArchitectureDecoder Only

Knowledge cutoff2025-01