Using Gemini Deep Research Preview on Google AI Studio
Implementation guide · Gemini 3.1 · Google DeepMind
Serverless
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. - 3You'll be billed $2.00/1M input, $12.00/1M output tokens.
Code Examples
Install
pip install google-genaiAPI key
GOOGLE_API_KEYModel ID
deep-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
Model prototyping and API access to Gemini models with inference playground
Pricing on Google AI Studio
| Type | Price (per 1M) |
|---|---|
| Input tokens | $2.00 |
| Output tokens | $12.00 |
Capabilities
VisionMultimodalReasoningFunction CallingTool UseStructured OutputsCode Execution
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.
Model Specs
Released2026-04-21
Context1M
ArchitectureDecoder Only