Deploy Gemma with Google Cloud  |  Google AI for Developers
Skip to main content
Models
Gemini
About
Docs
API reference
Pricing
Imagen
About
Docs
Pricing
Veo
About
Docs
Pricing
Gemma
About
Docs
Gemmaverse
Solutions
Build with Gemini
Gemini API
Google AI Studio
Customize Gemma open models
Gemma open models
Multi-framework with Keras
Fine-tune in Colab
Run on-device
Google AI Edge
Gemini Nano on Android
Chrome built-in web APIs
Build responsibly
Responsible GenAI Toolkit
Secure AI Framework
Code assistance
Android Studio
Chrome DevTools
Colab
Firebase
Google Cloud
JetBrains
Jules
VS Code
Community
Google AI Forum
Gemini for Research
/
English
Deutsch
Español – América Latina
Français
Indonesia
Italiano
Polski
Português – Brasil
Shqip
Tiếng Việt
Türkçe
Русский
עברית
العربيّة
فارسی
हिंदी
বাংলা
ภาษาไทย
中文 – 简体
中文 – 繁體
日本語
한국어
Sign in
Gemma
Gemma
Docs
Models
More
Gemma
Docs
Solutions
More
Code assistance
More
Community
More
Overview
Get started
Releases
Models
Core Gemma
Overview
Gemma 4 model card
Gemma 3 model card
Gemma 2 model card
Gemma 1 model card
Core Variants
Gemma 3n
Overview
Model card
DiffusionGemma
Overview
Model card
Diffusion Explained
Generate Output
FunctionGemma
Overview
Model card
Formatting and best practices
Function calling with Hugging Face Transformers
Full function calling sequence with FunctionGemma
Fine-tune FunctionGemma
EmbeddingGemma
Overview
Model card
Generate embeddings with Sentence Transformers
Fine-tune EmbeddingGemma
PaliGemma
Overview
v2 model card
v1 model card
Generate output with Keras
Fine-tune with JAX and Flax
Prompt and system instructions
ShieldGemma
Overview
ShieldGemma 2 Model card
ShieldGemma 1 Model card
Run Gemma
Fundamentals
Overview
Prompt Formatting
Legacy Gemma setup [Gemma 1, 2, and 3]
Legacy Prompt and system instructions [Gemma 1, 2, and 3]
Run locally with a Chat UI or integrate via API
LM Studio
Ollama
Run efficiently on Edge
LiteRT-LM
Llama.cpp
MLX
Build/Train in Python
Tunix (Tune-in-JAX)
Hugging Face Transformers
Keras
Unsloth
Deploy to Production / Enterprise
Gemini API
Google Cloud
Cloud GKE
Multi-Token Prediction (MTP)
Overview
Hugging Face Transformers
Core Capabilities
Text
Basic and multi-turn chat
Function calling
Visual data
Overview
Image understanding
Video understanding
Audio data
Thinking
Tuning guides
Overview
Tune using Hugging Face Transformers and QLoRA
Vision Tune using Hugging Face Transformers and QLoRA
Full model fine-tune using Hugging Face Transformers
Tune using Gemma library
Research and tools
RecurrentGemma
Overview
Inference using JAX and Flax
Fine-tune using JAX and Flax
Model card
DataGemma
Gemma Scope
Gemma-APS
Community
Gemmaverse
Discord
Legal
Terms of use
Gemma 4 license
Prohibited use
Intended use statement
Gemini
About
Docs
API reference
Pricing
Imagen
About
Docs
Pricing
Veo
About
Docs
Pricing
Gemma
About
Docs
Gemmaverse
Build with Gemini
Gemini API
Google AI Studio
Customize Gemma open models
Gemma open models
Multi-framework with Keras
Fine-tune in Colab
Run on-device
Google AI Edge
Gemini Nano on Android
Chrome built-in web APIs
Build responsibly
Responsible GenAI Toolkit
Secure AI Framework
Android Studio
Chrome DevTools
Colab
Firebase
Google Cloud
JetBrains
Jules
VS Code
Google AI Forum
Gemini for Research
Gemma 4 released with text, audio and image input and long up to 256K context window! Learn more
Home
Gemma
Models
Docs
Send feedback
Deploy Gemma with Google Cloud
The Google Cloud platform provides many options for deploying, serving,
and fine-tuning Gemma 4 open models, including the following:
Gemini Enterprise Agent Platform
Cloud Run
Google Kubernetes Engine (GKE)
Agent Development Kit (ADK)
Gemini Enterprise Agent Platform Training Clusters
MaxText
vLLM with TPUs
Sovereign Cloud
Gemini Enterprise Agent Platform
Gemini Enterprise Agent Platform is a Google Cloud platform for rapidly
building and scaling machine learning projects. Gemma 4 is available in Model
Garden, a curated collection of models on Gemini Enterprise Agent Platform.
You can test and deploy models directly from the console.
To learn more, refer to the following pages:
Agent Platform overview: Get started with Gemini Enterprise Agent
Platform.
Gemma with Gemini Enterprise Agent Platform: Use Gemma open models with
Gemini Enterprise Agent Platform.
Cloud Run
Cloud Run is a fully managed platform to run your code or containers on
top of Google's highly scalable infrastructure.
Deploy Gemma 4 on Cloud Run using GPUs for scale-to-zero, pay-per-use
inference.
For larger mode sizes, leverage advanced configurations with RTX 6000 Pro
GPUs and Model Streaming.
Google Kubernetes Engine (GKE)
Google Kubernetes Engine (GKE) is a managed Kubernetes service from Google
Cloud. Run Gemma 4 on GKE for enterprise-grade container orchestration.
Use TPUs and GPUs to serve models with high throughput and low latency.
Agent Development Kit (ADK)
Build and orchestrate AI agents with Gemma 4 and the Agent Development Kit
(ADK). Gemma 4's strong reasoning and function-calling capabilities make it
ideal for agentic workflows.
Gemini Enterprise Agent Platform Training Clusters
Fine-tune Gemma 4 using Gemini Enterprise Agent Platform Training
Clusters. Training Clusters provides optimized infrastructure for
large-scale training and fine-tuning of open models.
vLLM with TPUs
Serve Gemma 4 on Google Cloud TPUs for state-of-the-art serving
performance.
MaxText
Gemma 4 is supported in MaxText, a high-performance, arbitrary-sized JAX
LLM implementation for Google Cloud TPUs.
Sovereign Cloud
Gemma 4 is available on Sovereign Cloud solutions, providing enhanced
control and compliance for sensitive workloads.
Send feedback
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2026-07-02 UTC.
Need to tell us more?
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2026-07-02 UTC."],[],[]]
Terms
Privacy
Manage cookies
English
Deutsch
Español – América Latina
Français
Indonesia
Italiano
Polski
Português – Brasil
Shqip
Tiếng Việt
Türkçe
Русский
עברית
العربيّة
فارسی
हिंदी
বাংলা
ภาษาไทย
中文 – 简体
中文 – 繁體
日本語
한국어