Vertex AI Image Generation

Vertex AI supports two types of image generation:

1. Gemini Image Generation Models (Nano Banana 🍌) - Conversational image generation using generateContent API
2. Imagen Models - Traditional image generation using predict API

Property	Details
Description	Vertex AI Image Generation supports both Gemini image generation models
Provider Route on LiteLLM	vertex_ai/
Provider Doc	Google Cloud Vertex AI Image Generation ↗
Gemini Image Generation Docs	Gemini Image Generation ↗

Quick Start

Gemini Image Generation Models

Gemini image generation models support conversational image creation with features like:

• Text-to-Image generation
• Image editing (text + image → image)
• Multi-turn image refinement
• High-fidelity text rendering
• Up to 4K resolution (Gemini 3 Pro)

Gemini 2.5 Flash Image

import litellm

# Generate a single image
response = await litellm.aimage_generation(
    prompt="A nano banana dish in a fancy restaurant with a Gemini theme",
    model="vertex_ai/gemini-2.5-flash-image",
    vertex_ai_project="your-project-id",
    vertex_ai_location="us-central1",
    n=1,
    size="1024x1024",
)

print(response.data[0].b64_json)  # Gemini returns base64 images

Gemini 3 Pro Image Preview (4K output)

import litellm

# Generate high-resolution image
response = await litellm.aimage_generation(
    prompt="Da Vinci style anatomical sketch of a dissected Monarch butterfly",
    model="vertex_ai/gemini-3-pro-image-preview",
    vertex_ai_project="your-project-id",
    vertex_ai_location="us-central1",
    n=1,
    size="1024x1024",
    # Optional: specify image size for Gemini 3 Pro
    # imageSize="4K",  # Options: "1K", "2K", "4K"
)

print(response.data[0].b64_json)

Google Search Grounding

Gemini image models (e.g. gemini-3.1-flash-image-preview, gemini-3-pro-image-preview) support Google Search on /v1/images/generations. LiteLLM maps web_search_options or OpenAI-style web_search tools to Gemini's googleSearch tool on the underlying generateContent request.

Image generation with Google Search

import litellm

response = await litellm.aimage_generation(
    prompt="Generate an image of the latest iPhone design",
    model="vertex_ai/gemini-3.1-flash-image-preview",
    vertex_ai_project="your-project-id",
    vertex_ai_location="us-central1",
    web_search_options={},
)

print(response.data[0].b64_json)

Using OpenAI-style web_search tool

import litellm

response = await litellm.aimage_generation(
    prompt="Generate an image of the latest iPhone design",
    model="vertex_ai/gemini-3.1-flash-image-preview",
    vertex_ai_project="your-project-id",
    vertex_ai_location="us-central1",
    tools=[{"type": "web_search"}],
)

Via LiteLLM Proxy (/v1/images/generations):

Proxy request with web_search_options

curl -X POST 'http://localhost:4000/v1/images/generations' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer sk-1234' \
-d '{
    "model": "gemini-3.1-flash-image-preview",
    "prompt": "Generate an image of the latest iPhone design",
    "web_search_options": {}
}'

Passing imageConfig (Gemini models)

Gemini image generation models support the full ImageConfig object. Pass it as imageConfig on any /v1/images/generations request and LiteLLM will forward all fields verbatim to generationConfig.imageConfig.

Field	Type	Description
aspectRatio	string	"1:1", "16:9", "9:16", "4:3", "3:4", "4:5", "5:4", "2:3", "3:2", "21:9"
imageSize	string	"1K", "2K", "4K" (supported on Gemini 3 Pro and newer)
personGeneration	string	"DONT_ALLOW", "ALLOW_ADULT", "ALLOW_ALL"
imageOutputOptions	object	{"mimeType": "image/jpeg"|"image/png"|"image/webp", "compressionQuality": 0–100}

Passing imageConfig via Python SDK

import litellm

response = await litellm.aimage_generation(
    model="vertex_ai/gemini-3.1-flash-image",
    prompt="A nano banana on a desk",
    vertex_ai_project="your-project-id",
    vertex_ai_location="us-central1",
    imageConfig={
        "aspectRatio": "16:9",
        "imageSize": "2K",
        "personGeneration": "DONT_ALLOW",
        "imageOutputOptions": {
            "mimeType": "image/jpeg",
            "compressionQuality": 85,
        },
    },
)

Passing imageConfig via Proxy

curl -X POST 'http://localhost:4000/v1/images/generations' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer sk-1234' \
-d '{
    "model": "gemini-3.1-flash-image",
    "prompt": "A nano banana on a desk",
    "imageConfig": {
        "aspectRatio": "16:9",
        "imageSize": "2K",
        "personGeneration": "DONT_ALLOW",
        "imageOutputOptions": {
            "mimeType": "image/jpeg",
            "compressionQuality": 85
        }
    }
}'

You can also use flat params as shorthand for aspectRatio and imageSize:

Flat param shorthand

response = await litellm.aimage_generation(
    model="vertex_ai/gemini-3.1-flash-image",
    prompt="A nano banana on a desk",
    aspect_ratio="16:9",   # or aspectRatio="16:9"
    image_size="2K",       # or imageSize="2K"
    vertex_ai_project="your-project-id",
    vertex_ai_location="us-central1",
)

Flat params (aspect_ratio, image_size, aspectRatio, imageSize) override the same key inside imageConfig when both are present.

Imagen Models

Imagen Image Generation

import litellm

# Generate a single image
response = await litellm.aimage_generation(
    prompt="An olympic size swimming pool with crystal clear water and modern architecture",
    model="vertex_ai/imagen-4.0-generate-001",
    vertex_ai_project="your-project-id",
    vertex_ai_location="us-central1",
    n=1,
    size="1024x1024",
)

print(response.data[0].b64_json)  # Imagen also returns base64 images

LiteLLM Proxy

1. Configure your config.yaml

Vertex AI Image Generation Configuration

model_list:
  - model_name: vertex-imagen
    litellm_params:
      model: vertex_ai/imagen-4.0-generate-001
      vertex_ai_project: "your-project-id"
      vertex_ai_location: "us-central1"
      vertex_ai_credentials: "path/to/service-account.json"  # Optional if using environment auth

2. Start LiteLLM Proxy Server

Start LiteLLM Proxy Server

litellm --config /path/to/config.yaml

# RUNNING on http://0.0.0.0:4000

3. Make requests with OpenAI Python SDK

Basic Image Generation via Proxy

from openai import OpenAI

# Initialize client with your proxy URL
client = OpenAI(
    base_url="http://localhost:4000",  # Your proxy URL
    api_key="your-proxy-api-key"      # Your proxy API key
)

# Generate image
response = client.images.generate(
    model="vertex-imagen",
    prompt="An olympic size swimming pool with crystal clear water and modern architecture",
)

print(response.data[0].url)

Supported Models

Gemini Image Generation Models

• vertex_ai/gemini-2.5-flash-image - Fast, efficient image generation (1024px resolution)
• vertex_ai/gemini-3.1-flash-image-preview - Fast image generation with Google Search grounding
• vertex_ai/gemini-3-pro-image-preview - Advanced model with 4K output, Google Search grounding, and thinking mode
• vertex_ai/gemini-2.0-flash-preview-image - Preview model
• vertex_ai/gemini-2.5-flash-image-preview - Preview model

Imagen Models

• vertex_ai/imagegeneration@006 - Legacy Imagen model
• vertex_ai/imagen-4.0-generate-001 - Latest Imagen model
• vertex_ai/imagen-3.0-generate-001 - Imagen 3.0 model

tip

We support ALL Vertex AI Image Generation models, just set model=vertex_ai/<any-model-on-vertex_ai> as a prefix when sending litellm requests

For the complete and up-to-date list of supported models, visit: https://models.litellm.ai/