Using Gemini 3.1 Flash Lite Image (Nano Banana 2 Lite) on GCP Vertex AI
Implementation guide · Gemini 3.1 · Google DeepMind
GCP Vertex AI exposes Gemini 3.1 Flash Lite Image (Nano Banana 2 Lite) through model ID gemini-3.1-flash-lite-image. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-10-19. Next refresh: weekly.
Quick Start
- 1
- 2Use the GCP Vertex AI SDK or REST API to call
gemini-3.1-flash-lite-image— see the documentation for request format. - 3
Code Examples
pip install google-cloud-aiplatformGOOGLE_CLOUD_PROJECTgemini-3.1-flash-lite-imageFor 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-image")
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 |
| Image input | $30.00 |
Capabilities
About Gemini 3.1 Flash Lite Image (Nano Banana 2 Lite)
Gemini 3.1 Flash Lite Image (Nano Banana 2 Lite; API id gemini-3.1-flash-lite-image) is Google's efficiency-focused image generation/editing model. Inputs text/image/video/PDF; outputs image+text. FP limits 65536/4096. Paid: $0.25/1M input, $1.50/1M text output, $30/1M image output (~$0.0336/1K image).