Introducing Colab Enterprise, combining the ease of use of Colab with Google Cloud enterprise security and compliance. Learn more.
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Vertex AI Notebooks

Choose from Colab Enterprise or Vertex AI Workbench. Access every capability in Vertex AI Platform to work across the entire data science workflow—from data exploration to prototype to production. 

  • Natively analyze your data with a reduction in context switching between services

  • Data to training at scale. Build and train models 5x faster, compared to traditional notebooks

  • Scale up model development with simple connectivity to Vertex AI services


Easy exploration and analysis

Simplified access to data and in-notebook access to machine learning with BigQuery, Dataproc, Spark, and Vertex AI integration.

Rapid prototyping and model development

Take advantage of the power of infinite compute with Vertex AI Training for experimentation and prototyping, to go from data to training at scale.

End-to-end notebook workflows

Using Colab Enterprise or Vertex AI Workbench you can implement your training and deployment workflows on Vertex AI from one place.

Key features

Key features

Colab Enterprise

Colab Enterprise combines the notebook developed by Google Research and used by over 7 million data scientists with Google Cloud enterprise level security and compliance. Get started quickly with a zero-config, serverless, and collaborative environment. 

AI-powered code assistance features like code completion and code generation make it easier to build AI/ML models in Python, reducing the need to write repetitive code, so you can focus on your data and models.

Vertex AI Workbench

Vertex AI Workbench provides a JupyterLab experience and advanced customization capabilities. 

Fully managed compute

Vertex AI notebooks provide fully managed, scalable, enterprise-ready compute infrastructure with security controls and user management capabilities.

Interactive data and ML experience

Explore data and train ML models with easy connections to Google Cloud's big data solutions.

Portal to complete end-to-end ML training

Develop and deploy AI solutions on Vertex AI with minimal transition.


Technical resources

Google Cloud Basics
Colab Enterprise documentation

Explore Colab Enterprise features and create a notebook to get started.

Google Cloud Basics
Vertex AI Workbench documentation

Learn more about Vertex AI Workbench. 

Google Cloud Basics
Vertex AI documentation

Explore Vertex AI product documentation, from introductory to advanced.

All features

All features

Simplified data access Extensions will seamlessly connect to the entire data estate including BigQuery, Data Lake, Dataproc, and Spark. Seamlessly scale up or scale out depending on your analytic and AI needs.
Explore data sources using a catalog Write SQL, Spark queries from a syntax-aware, auto-complete enabled notebook cell.
Data visualization Integrated, intelligent visualization tools will provide easy insights into data. 
Hands-off, cost-effective infrastructure All aspects of the compute are managed. Idle timeout and auto shutdown will optimize total cost of ownership.
Enterprise security, simplified Out-of-the-box Google Cloud security controls. Single sign-on and simple authentication to other Google Cloud services.
Data Lake and Spark in one place Whether you use TensorFlow, PyTorch, or Spark, you can run any engine from Vertex AI Workbench. 
Deep Git, training, and MLOps integration With few clicks, plug notebooks into established Ops workflows. Use notebooks for distributed training, hyper-parameter optimization, or scheduled or triggered continuous training. Deep integration with Vertex AI services brings MLOps into the notebook without the need to rewrite code or new workflows.
Seamless CI/CD Kubeflow Pipelines integration to use Notebooks as an ideal, tested, and verified deployment target. 
Notebook viewer Share output of periodically updated notebook cells for reporting and bookkeeping purposes.



Colab Enterprise pricing details.

Vertex AI Workbench pricing details.

Pricing models are based upon compute and services based on the infrastructure you use, as well as other services consumed from within Vertex AI notebooks.