Supported GPU machines for Cluster Director

This document describes the GPU-accelerated machine series that are available in Cluster Director. You can use these machine series only for compute nodes to run large-scale artificial intelligence (AI), machine learning (ML), and high performance computing (HPC) workloads. For an overview of GPU architecture, ideal use cases, and pricing in Google Cloud, see Understand GPUs.

GPU machine types are available in zones where both Cluster Director and the GPU machine type are available, except for AI zones.

A4X Max and A4X machine series

The A4X Max and A4X machine series run on an exascale platform based on NVIDIA's rack-scale architecture and are optimized for compute-intensive, memory-intensive, and network-bound ML training and HPC workloads. A4X Max and A4X differ in their GPU and networking components. A4X Max is available only as bare metal instances, which provide direct access to the host server's CPU and memory without the Compute Engine hypervisor layer.

You can pair compute nodes that use the A4X Max or A4X machine series with login nodes that use the C4A or N2 machine series. A4X Max and A4X instances require Hyperdisk Balanced boot disks.

A4X Max machine type (bare metal)

A4X Max accelerator-optimized machine types use NVIDIA GB300 Grace Blackwell Ultra Superchips (nvidia-gb300) and are ideal for foundation model training and serving. A4X Max machine types are available as bare metal instances.

A4X Max is an exascale platform based on NVIDIA GB300 NVL72. Each machine has two sockets with NVIDIA Grace CPUs with Arm Neoverse V2 cores. These CPUs are connected to four NVIDIA B300 Blackwell GPUs with fast chip-to-chip (NVLink-C2C) communication. For information about machine type limitations, see A4X Max and A4X limitations.

The following table lists the specifications for the A4X Max machine type:

Note: To use A4X Max machine types in your cluster, you must reserve capacity through your account team and use the reserved capacity to create instances. For more information about the ways you can create A4X Max instances in a cluster, see Choose a consumption option.

Machine type	vCPU count	Instance memory (GB)	Attached Local SSD (GiB)	Physical NIC count	Maximum network bandwidth (Gbps)	NVIDIA GB300 GPU count	GPU memory (GB HBM3e)
a4x-maxgpu-4g-metal	144	960	12,000	6	3,600	4	1,116

The following notes apply to the preceding table:

• vCPU count: a vCPU is implemented as a single hardware hyper-thread on one of the available CPU platforms.
• Maximum network bandwidth: maximum egress bandwidth can't exceed the number given. Actual egress bandwidth depends on the destination IP address and other factors. For more information about network bandwidth, see Network bandwidth.
• GPU memory: GPU memory is the memory on a GPU device that can be used for temporary storage of data. It is separate from the instance's memory and is specifically designed to handle the higher bandwidth demands of your graphics-intensive workloads.

A4X machine type

A4X accelerator-optimized machine types use NVIDIA GB200 Grace Blackwell Superchips (nvidia-gb200) and are ideal for foundation model training and serving.

A4X is an exascale platform based on NVIDIA GB200 NVL72. Each machine has two sockets with NVIDIA Grace CPUs with Arm Neoverse V2 cores. These CPUs are connected to four NVIDIA B200 Blackwell GPUs with fast chip-to-chip (NVLink-C2C) communication. For information about machine type limitations, see A4X Max and A4X limitations.

The following table lists the specifications for the A4X machine type:

Note: To use A4X machine types in your cluster, you must reserve capacity through your account team and use the reserved capacity to create VMs. For more information about the ways you can create A4X VMs in a cluster, see Choose a consumption option.

Machine type	vCPU count	Instance memory (GB)	Attached Local SSD (GiB)	Physical NIC count	Maximum network bandwidth (Gbps)	NVIDIA GB200 GPU count	GPU memory (GB HBM3e)
a4x-highgpu-4g	140	884	12,000	6	2,000	4	744

The following notes apply to the preceding table:

• vCPU count: a vCPU is implemented as a single hardware hyper-thread on one of the available CPU platforms.
• Maximum network bandwidth: maximum egress bandwidth can't exceed the number given. Actual egress bandwidth depends on the destination IP address and other factors. For more information about network bandwidth, see Network bandwidth.
• GPU memory: GPU memory is the memory on a GPU device that can be used for temporary storage of data. It is separate from the instance's memory and is specifically designed to handle the higher bandwidth demands of your graphics-intensive workloads.

A4 machine series

A4 accelerator-optimized machine types have NVIDIA B200 Blackwell GPUs (nvidia-b200) attached and are ideal for foundation model training and serving. For information about machine type limitations, see A4 limitations.

In Cluster Director, you must pair A4 compute nodes with login nodes that use the N2 machine series. A4 instances require Hyperdisk Balanced boot disks. The following table lists the specifications for the A4 machine type:

Note: To use A4 machine types in your cluster, you must reserve capacity to create VMs, create Spot VMs, or create Flex-start VMs. For more information about the ways you can create A4 VMs in a cluster, see Choose a consumption option.

Machine type	vCPU count	Instance memory (GB)	Attached Local SSD (GiB)	Physical NIC count	Maximum network bandwidth (Gbps)	NVIDIA B200 Blackwell GPU count	GPU memory (GB HBM3e)
a4-highgpu-8g	224	3,968	12,000	10	3,600	8	1,440

The following notes apply to the preceding table:

• vCPU count: a vCPU is implemented as a single hardware hyper-thread on one of the available CPU platforms.
• Maximum network bandwidth: maximum egress bandwidth can't exceed the number given. Actual egress bandwidth depends on the destination IP address and other factors. For more information about network bandwidth, see Network bandwidth.
• GPU memory: GPU memory is the memory on a GPU device that can be used for temporary storage of data. It is separate from the instance's memory and is specifically designed to handle the higher bandwidth demands of your graphics-intensive workloads.

A3 machine series

The A3 machine series uses NVIDIA H100 or H200 SXM GPUs and is suitable for a wide range of large model training and inference workloads. In Cluster Director, you must pair A3 compute nodes with login nodes that use the N2 machine series.

Cluster Director supports the A3 machine types that are described in the following sections.

A3 Ultra machine type

A3 Ultra machine types have NVIDIA H200 SXM GPUs (nvidia-h200-141gb) attached and provide the highest network performance in the A3 series. A3 Ultra machine types are ideal for foundation model training and serving. For information about machine type limitations, see A3 Ultra limitations.

In Cluster Director, A3 Ultra instances require Hyperdisk Balanced boot disks. The following table lists the specifications for the A3 Ultra machine type:

Note: To use A3 Ultra machine types in your cluster, you must reserve capacity to create VMs, create Spot VMs, or create Flex-start VMs. For more information about the ways to create A3 Ultra VMs in a cluster, see Choose a consumption option.

Machine type	vCPU count	Instance memory (GB)	Attached Local SSD (GiB)	Physical NIC count	Maximum network bandwidth (Gbps)	NVIDIA H200 GPU count	GPU memory (GB HBM3e)
a3-ultragpu-8g	224	2,952	12,000	10	3,600	8	1128

The following notes apply to the preceding table:

• vCPU count: a vCPU is implemented as a single hardware hyper-thread on one of the available CPU platforms.
• Maximum network bandwidth: maximum egress bandwidth can't exceed the number given. Actual egress bandwidth depends on the destination IP address and other factors. For more information about network bandwidth, see Network bandwidth.
• GPU memory: GPU memory is the memory on a GPU device that can be used for temporary storage of data. It is separate from the instance's memory and is specifically designed to handle the higher bandwidth demands of your graphics-intensive workloads.

A3 Mega machine type

A3 Mega machine types have NVIDIA H100 SXM GPUs and are ideal for large model training and multi-host inference. For information about machine type limitations, see A3 Mega limitations.

In Cluster Director, A3 Mega instances support Balanced Persistent Disk, SSD (performance) Persistent Disk, Hyperdisk Balanced, Hyperdisk ML, Hyperdisk Extreme, or Hyperdisk Throughput boot disks. The following table lists the specifications for the A3 Mega machine type:

Note: To use A3 Mega machine types in your cluster, you must reserve capacity to create VMs, create Spot VMs, or create Flex-start VMs. For more information about the ways to create A3 Mega VMs in a cluster, see Choose a consumption option.

Machine type	vCPU count	Instance memory (GB)	Attached Local SSD (GiB)	Physical NIC count	Maximum network bandwidth (Gbps)	NVIDIA H100 GPU count	GPU memory (GB HBM3)
a3-megagpu-8g	208	1,872	6,000	9	1,800	8	640

The following notes apply to the preceding table:

• vCPU count: a vCPU is implemented as a single hardware hyper-thread on one of the available CPU platforms.
• Maximum network bandwidth: maximum egress bandwidth can't exceed the number given. Actual egress bandwidth depends on the destination IP address and other factors. For more information about network bandwidth, see Network bandwidth.
• GPU memory: GPU memory is the memory on a GPU device that can be used for temporary storage of data. It is separate from the instance's memory and is specifically designed to handle the higher bandwidth demands of your graphics-intensive workloads.

What's next

• Supported CPU machines for Cluster Director

• Supported TPU machines for Cluster Director

• Supported OS images for Cluster Director

• Try out Cluster Director