T5Gemma on GCP Vertex AI

T5Gemma · Google DeepMind

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Last refreshed 2026-06-30. Next refresh: weekly.

Why use T5Gemma on GCP Vertex AI?

GCP Vertex AI offers T5Gemma with free input token pricing. Vertex AI is Google Cloud's managed AI platform, offering access to Gemini models and hundreds of partner models alongside tools for fine-tuning, grounding, vector search, and end-to-end MLOps pipelines.

Input / 1M
Free
Output / 1M
Free
Cache
Not sourced
Batch
Not sourced

Setup recipe

Python + curl
Install
pip install google-cloud-aiplatform
Auth
export GOOGLE_CLOUD_PROJECT=...
Call
import os
import vertexai
from vertexai.generative_models import GenerativeModel
vertexai.init(project=os.environ["GOOGLE_CLOUD_PROJECT"], location="us-central1")
Model ID
t5gemma

Request example

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("t5gemma")
response = model.generate_content("Hello")
print(response.text)

Gotchas

  • 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".
  • The examples expect GOOGLE_CLOUD_PROJECT; rename it only if your application config maps the new variable.

Pricing

TypePrice (per 1M)
Input tokensFree
Output tokensFree

Capabilities

JSON / Tool useStructured Outputs

About T5Gemma

T5Gemma is Google's open encoder-decoder model family based on Gemma 2, not a Gemma 3 proprietary decoder-only model.

Get Started

DocsPortalPricing

Model Specs

Released2025-07-09
Parameters2B
ArchitectureEncoder-Decoder

Provider

GCP Vertex AI

Google Cloud Platform (GCP)

All models on GCP Vertex AI →Provider setup guide →