Using Gemini 3.5 Flash-Lite on Google AI Studio
Implementation guide · Gemini 3.5 · Google DeepMind
Google AI Studio exposes Gemini 3.5 Flash-Lite through model ID gemini-3.5-flash-lite. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-07-21. Next refresh: weekly.
Quick Start
- 1
- 2Use the Google AI Studio SDK or REST API to call
gemini-3.5-flash-lite— see the documentation for request format. - 3
Code Examples
pip install google-genaiGOOGLE_API_KEYgemini-3.5-flash-liteUse 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-3.5-flash-lite",
contents="Hello"
)
print(response.text)Pricing on Google AI Studio
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.30 |
| Output tokens | $2.50 |
Capabilities
About Gemini 3.5 Flash-Lite
Gemini 3.5 Flash-Lite is Google DeepMind's generally available multimodal model in the Gemini 3.5 family. It accepts text, image, video, audio, and PDF inputs and returns text, with a 1,048,576-token context window, up to 65,536 output tokens, and Gemini API support for code execution, prompt caching, and batch processing. Compare it for Coding, Agents, Long context, Vision, and JSON / Tool use. In Google AI Studio, select Gemini 3.5 Flash-Lite when lower token cost and high throughput are the priority; select Gemini 3.6 Flash when higher capability matters more.