To run artificial intelligence (AI), machine learning (ML), or high performancecomputing (HPC) workloads, you can deploy AI-optimized VMs and clusters ofA4X, A4, and A3 Ultra machines. For more information about the features ofthese machines that enable you to run large-scale AI/MLclusters, seeCluster management overview.

Note: This guide only applies to the A4X, A4, and A3 Ultramachine types. Guidance for other machine types is out of scope for thisdocumentation. We recommend that you consult the relevant documentation for yourchoice of machine type. To identify the VM and cluster creation guide for othermachine types, seeChoose a deployment strategy.

You can create A4X, A4, and A3 Ultra VMs directly fromCompute Engine, or through other services that run on Compute Engineinstances like Cluster Toolkit or Google Kubernetes Engine.

For the most appropriate option to create your VMs or clusters for your usecase, choose one of the following:

Option	Use case
Cluster Toolkit	You want to use open-source software that simplifies the process for you to deploy both Slurm and GKE clusters. Cluster Toolkit is designed to be highly customizable and extensible. To learn more, see the following: Create an AI-optimized Slurm cluster Create an AI-optimized Google Kubernetes Engine cluster with default configuration
GKE	You want maximum flexibility in configuring your Google Kubernetes Engine cluster based on the needs of your workload. To learn more, seeCreate a custom AI-optimized Google Kubernetes Engine cluster.
Use Compute Engine	You want full control of the infrastructure layer so that you can set up your own orchestrator. To learn more, see the following: Create an AI-optimized instance Create A4X Create A4 or A3 Ultra Create AI-optimized instances in bulk Create A4X Create A4 or A3 Ultra Create an AI-optimized MIG Create A4X Create A4 or A3 Ultra