Using Gemini Deep Research Preview on Google AI Studio
Implementation guide · Gemini 3.1 · Google DeepMind
Quick Start
- 1
- 2Use the Google AI Studio SDK or REST API to call
deep-research-preview-04-2026— see the documentation for request format. - 3
Code Examples
pip install google-genaiGOOGLE_API_KEYdeep-research-preview-04-2026Use 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="deep-research-preview-04-2026",
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.
Pricing on Google AI Studio
| Type | Price (per 1M) |
|---|---|
| Input tokens | $2.00 |
| Output tokens | $12.00 |
Capabilities
About Gemini Deep Research Preview
Google's agentic deep research model built on Gemini 3.1 Pro, released April 21, 2026. Designed for speed and efficiency in autonomous multi-step research: ingests text, images, PDFs, audio, and video to produce comprehensive cited reports from public web sources and private workspace data. Supports collaborative planning, visualization, MCP servers, and File Search. Context window: 1M tokens; max output: 65,536 tokens. Runs at Gemini 3.1 Pro rates ($2.00/$12.00 per MTok). API ID: deep-research-preview-04-2026.