Using Gemma 7B on GCP Vertex AI

Implementation guide · Gemma · Google DeepMind

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GCP Vertex AI exposes Gemma 7B through model ID gemma-7b. 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
Create an account at GCP Vertex AI and generate an API key.
2
Use the GCP Vertex AI SDK or REST API to call gemma-7b — see the documentation for request format.
3
You'll be billed $0.10/1M input, $0.30/1M output tokens. See full pricing.

API Portal Documentation Pricing

Code Examples

Install

pip install google-cloud-aiplatform

API key

GOOGLE_CLOUD_PROJECT

Model ID

gemma-7b

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("gemma-7b")
response = model.generate_content("Hello")
print(response.text)

Pricing on GCP Vertex AI

Type	Price (per 1M)
Input tokens	$0.10
Output tokens	$0.30

Capabilities

Structured Outputs

About Gemma 7B

Gemma 7B is Google DeepMind's Gemma model. It offers an 8K-token context window with weights openly available for self-hosting.

Full model details →

Model Specs

Released2024-02-21

Parameters7B

Context8k

ArchitectureDecoder Only

Knowledge cutoff2023-04

Google Cloud Platform (GCP)

Mountain View, California, United States