Using Gemini 3.1 Flash Lite Preview on GCP Vertex AI

Implementation guide · Gemini 3.1 · Google DeepMind

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GCP Vertex AI exposes Gemini 3.1 Flash Lite Preview through model ID gemini-3.1-flash-lite-preview. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.

Last refreshed 2026-06-15. Next refresh: weekly.

Quick Start

1
Create an account at GCP Vertex AI and generate an API key.
2
Use the GCP Vertex AI SDK or REST API to call gemini-3.1-flash-lite-preview — see the documentation for request format.
3
You'll be billed $0.25/1M input, $1.50/1M output tokens. See full pricing.

API Portal Documentation Pricing

Code Examples

Install

pip install google-cloud-aiplatform

API key

GOOGLE_CLOUD_PROJECT

Model ID

gemini-3.1-flash-lite-preview

For Google-published models use the model name directly, e.g. "gemini-2.0-flash-001". For third-party publishers (Anthropic, Meta, etc.) use the full publisher path, e.g. "publishers/anthropic/models/claude-3-5-sonnet-v2@20241022".

import os
import vertexai
from vertexai.generative_models import GenerativeModel

# Reads GOOGLE_CLOUD_PROJECT from env; authenticates via Application Default Credentials
vertexai.init(project=os.environ["GOOGLE_CLOUD_PROJECT"], location="us-central1")
model = GenerativeModel("gemini-3.1-flash-lite-preview")
response = model.generate_content("Hello")
print(response.text)

Pricing on GCP Vertex AI

Type	Price (per 1M)
Input tokens	$0.25
Output tokens	$1.50

Capabilities

VisionMultimodalJSON / Tool useStructured OutputsCode Execution

About Gemini 3.1 Flash Lite Preview

Preview-stage Gemini 3.1 Flash-Lite model shut down on 2026-05-25; use gemini-3.1-flash-lite GA instead.

Full model details →

Model Specs

Released2026-03-03

Context1m

ArchitectureDecoder Only

Knowledge cutoff2025-01

Google Cloud Platform (GCP)

Mountain View, California, United States