Last refreshed 2026-05-19. Next refresh: weekly.
Why use Gemini Deep Research on Google AI Studio?
Google AI Studio offers Gemini Deep Research with competitive pricing. 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.
Input / 1M
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Output / 1M
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Cache
Not sourced
Batch
Not sourced
Setup recipe
Python + curlInstall
pip install google-genaiAuth
export GOOGLE_API_KEY=...Call
import os
from google import genai
client = genai.Client(api_key=os.environ["GOOGLE_API_KEY"])
response = client.models.generate_content(Model ID
gemini-deep-researchRequest example
import os
from google import genai
client = genai.Client(api_key=os.environ["GOOGLE_API_KEY"])
response = client.models.generate_content(
model="gemini-deep-research",
contents="Hello"
)
print(response.text)Gotchas
- Use the model name directly, e.g. "gemini-2.0-flash", "gemini-1.5-pro", or "gemini-2.5-pro-preview-05-06".
- The examples expect GOOGLE_API_KEY; rename it only if your application config maps the new variable.
Capabilities
Function CallingTool UseStructured Outputs
About Gemini Deep Research
Gemini Deep Research is Google DeepMind's Gemini 2.5 model. It offers a 128K-token context window.
FAQ
What is the context window for Gemini Deep Research on Google AI Studio?
Gemini Deep Research supports a 128,000 token context window on Google AI Studio.
Who created Gemini Deep Research?
Gemini Deep Research was created by Google DeepMind as part of the Gemini 2.5 model family.
Is Gemini Deep Research open source?
Gemini Deep Research is not open source; the seed data lists it as proprietary.
Get Started
Model Specs
Released2024-12-11
Context128K
ArchitectureDecoder Only
Knowledge cutoff2025-01