Using Imagen Product Recontext on GCP Vertex AI
Implementation guide · Imagen · Google DeepMind
Serverless
GCP Vertex AI exposes Imagen Product Recontext through model ID imagen-product-recontext. 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
- 2Use the GCP Vertex AI SDK or REST API to call
imagen-product-recontext— see the documentation for request format.
Code Examples
Install
pip install google-cloud-aiplatformAPI key
GOOGLE_CLOUD_PROJECTModel ID
imagen-product-recontextFor 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("imagen-product-recontext")
response = model.generate_content("Hello")
print(response.text)Pricing on GCP Vertex AI
Capabilities
VisionMultimodal
About Imagen Product Recontext
Imagen Product Recontext is Google DeepMind's Imagen model focused on image generation. It was released 2024-10-01.
Model Specs
Released2024-10-01