Using CodeGemma on Google Vertex AI on GCP Vertex AI

Implementation guide · CodeGemma · Google DeepMind

ServerlessOpen Weights

GCP Vertex AI exposes CodeGemma on Google Vertex AI through model ID vertex-codegemma. 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 vertex-codegemma — see the documentation for request format.
  3. 3
    You'll be billed $0.13/1M input, $0.38/1M output tokens. See full pricing.
API PortalDocumentationPricing

Code Examples

Install
pip install google-cloud-aiplatform
API key
GOOGLE_CLOUD_PROJECT
Model ID
vertex-codegemma

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("vertex-codegemma")
response = model.generate_content("Hello")
print(response.text)

Pricing on GCP Vertex AI

TypePrice (per 1M)
Input tokens$0.13
Output tokens$0.38

Capabilities

Structured Outputs

About CodeGemma on Google Vertex AI

CodeGemma on Google Vertex AI is Google DeepMind's CodeGemma model. It offers an 8K-token context window with weights openly available for self-hosting.

Full model details →

Model Specs

Released2024-05-03
Parameters7B
Context8k
ArchitectureDecoder Only

Provider

GCP Vertex AI

Google Cloud Platform (GCP)

Mountain View, California, United States