Using Nano Banana 2 (Gemini 3.1 Flash Image Preview) on GCP Vertex AI

Implementation guide · Gemini 3.1 · Google DeepMind

Serverless

GCP Vertex AI exposes Nano Banana 2 (Gemini 3.1 Flash Image Preview) through model ID gemini-3.1-flash-image-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. 1
    Create an account at GCP Vertex AI and generate an API key.
  2. 2
    Use the GCP Vertex AI SDK or REST API to call gemini-3.1-flash-image-preview — see the documentation for request format.
  3. 3
    You'll be billed $0.50/1M input, $60.00/1M output tokens. See full pricing.

Code Examples

Install
pip install google-cloud-aiplatform
API key
GOOGLE_CLOUD_PROJECT
Model ID
gemini-3.1-flash-image-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-image-preview")
response = model.generate_content("Hello")
print(response.text)

Pricing on GCP Vertex AI

TypePrice (per 1M)
Input tokens$0.50
Output tokens$60.00

Capabilities

No model capability flags are currently sourced.

About Nano Banana 2 (Gemini 3.1 Flash Image Preview)

Preview release of Nano Banana 2 for Gemini 3.1 Flash Image. Google released the GA gemini-3.1-flash-image model on 2026-05-28 and will retire this preview API ID on 2026-06-25.

Model Specs

Released2026-03-03
Context66k
ArchitectureDecoder Only
Knowledge cutoff2025-01

Provider

GCP Vertex AI

Google Cloud Platform (GCP)

Mountain View, California, United States