Machine families

This document describes the machine families, machine series, and machine types that you can choose from to create a virtual machine (VM) instance with the resources you need. When you create a VM, you select a machine type from a machine family that determines the resources available to that VM. There are several machine families you can choose from and each machine family is further organized into machine series and predefined machine types within each series. For example, within the N2 series in the general-purpose machine family, you can select the n2-standard-4 machine type.

All machine series support preemptible VMs, with the exception of the M2 machine series.

Note: This is a list of Compute Engine machine families. For a detailed explanation of each family, see the following pages:
  • General-purpose —best price-performance ratio for a variety of workloads.
  • Compute-optimized —highest performance per core on Compute Engine and optimized for compute-intensive workloads.
  • Memory-optimized —ideal for memory-intensive workloads, offering more memory per core than other machine families, with up to 12 TB of memory.
  • Accelerator-optimized —ideal for massively parallelized Compute Unified Device Architecture (CUDA) compute workloads, such as machine learning (ML) and high performance computing (HPC). This family is the best option for workloads that require GPUs.

In summary, this document describes the following terms:

  • Machine family: A curated set of processor and hardware configurations optimized for specific workloads. When you create a VM instance, you choose a predefined or custom machine type from your preferred machine family.

  • Series: Machine families are further classified by series and generation. For example, the N1 series within the general-purpose machine types is the older version of the N2 series. Generally, generations of a machine series use a higher number to describe the newer generation. For example, the N2 series is the newer generation of the N1 series.

  • Machine type: Every machine series has predefined machine types that provide a set of resources for your VM. If a predefined machine type does not meet your needs, you can also create a custom machine type.

Try it for yourself

If you're new to Google Cloud, create an account to evaluate how Compute Engine performs in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

Try Compute Engine free

Billing

You are billed for the resources that a VM instance uses. VMs are billed as described in the VM instance pricing page. Specifically, you are billed for each vCPU and GB of memory individually, as described in resource-based billing model. Applicable discounts, such as sustained use discounts and committed use discounts apply.

To see the calculated hourly and monthly cost for each machine type, see VM instance pricing.

Machine family categories

The general-purpose machine family offers several machine series with the best price-performance ratio for a variety of workloads.

  • Cost-optimized E2 machine series has up to 32 vCPUs with up to 128 GB of memory with a maximum of 8 GB per vCPU. The E2 machine series has a predefined CPU platform, running either an Intel processor or the second generation AMD EPYC Rome processor. The processor is selected for you when you create the VM. This machine series provides a variety of compute resources for the lowest price on Compute Engine, especially when paired with committed-use discounts.
  • N2 machine series has up to 128 vCPUs, 8 GB of memory per vCPU, and is available on the Intel Ice Lake and Cascade Lake CPU platforms.
  • N2D machine series has up to 224 vCPUs, 8 GB of memory per vCPU, and is available on second generation AMD EPYC Rome platforms.
  • Tau T2D machine series has up to 60 vCPUs, 4 GB of memory per vCPU, and is available on third generation AMD EPYC Milan processors. The Tau T2D machine series has cluster-threading disabled, therefore a vCPU is equivalent to an entire core.
  • N1 machine series have up to 96 vCPUs, 6.5 GB of memory per vCPU, and are available on Intel Sandy Bridge, Ivy Bridge, Haswell, Broadwell, and Skylake CPU platforms.

The E2 and N1 series are shared-core machine series. Machine types in these series timeshare a physical core which can be a cost-effective method for running small, non-resource intensive apps.

  • E2: offers 2 vCPUs for short periods of bursting.

  • N1: offers f1-micro and g1-small shared-core machine types which have up to 1 vCPU available for short periods of bursting.

The compute-optimized machine family has the highest performance per core on Compute Engine and is optimized for compute-intensive workloads. Machine series in this family runs on an Intel Scalable Processor (Cascade Lake) and can sustain up to 3.8 GHz all-core turbo.

  • C2 VMs offer up to 60 vCPUs, 4 GB of memory per vCPU, and are available on the Intel Cascade Lake CPU platform.
  • C2D VMs offer up to 112 vCPUs, 4 GB of memory per vCPU, and are available on the third generation AMD EPYC Milan platform.

The memory-optimized machine family has machine series that are ideal for memory-intensive workloads. This family offers more memory per core than any other machine family, with up to 12 TB of memory.

The accelerator-optimized machine family is ideal for massively parallelized Compute Unified Device Architecture (CUDA) compute workloads, such as machine learning (ML) and high performance computing (HPC). This family is the optimal choice for workloads that require GPUs.

Machine family and series recommendations

The following table provides recommendations for different workloads.

Workload type
General-purpose workloads Optimized workloads
Cost-optimized Balanced Scale-out optimized Memory-optimized Compute-optimized Accelerator-optimized
E2 N2, N2D, N1 Tau T2D M2, M1 C2, C2D A2
Day-to-day computing at a lower cost Balanced price/performance across a wide range of VM shapes Best performance/cost for scale-out workloads Ultra high-memory workloads Ultra high performance for compute-intensive workloads Optimized for high performance computing workloads
  • Web serving
  • App serving
  • Back office apps
  • Small-medium databases
  • Microservices
  • Virtual desktops
  • Development environments
  • Web serving
  • App serving
  • Back office apps
  • Medium-large databases
  • Cache
  • Media/streaming
  • Scale-out workloads
  • Web serving
  • Containerized microservices
  • Media transcoding
  • Large-scale Java applications
  • Medium-large in-memory databases such as SAP HANA
  • In-memory databases and in-memory analytics
  • Microsoft SQL Server and similar databases
  • Compute-bound workloads
  • High-performance web serving
  • Gaming (AAA game servers)
  • Ad serving
  • High-performance computing (HPC)
  • Media transcoding
  • AI/ML
  • CUDA-enabled ML training and inference
  • HPC
  • Massive parallelized computation
  • See VM recommendations to learn about selecting the right machine type for your workload.

    After you create a VM, you can use rightsizing recommendations to optimize resource utilization. For more information, see Applying machine type recommendations for VM instances.

    Machine series comparison

    Use the following table to compare each machine family and determine which one is appropriate for your workload. If, after reviewing this section, you are still unsure which family is best for your workload, start with the general-purpose machine family. See CPU platforms for details about all supported processors.

    To learn how your selection affects the performance of persistent disks attached to your VMs, see Configuring your persistent disks and VMs.

    Machine series vCPUs Memory (per vCPU) Processors Custom VMs Local SSDs Sustained-use discounts Preemptible VMs
    E2* General-purpose 2–32 0.5–8 GB
    • Skylake
    • Broadwell
    • Haswell
    • AMD EPYC Rome
    Yes No No Yes
    E2* shared-core 0.25–1 0.5–8 GB
    • Skylake
    • Broadwell
    • Haswell
    • AMD EPYC Rome
    Yes No No Yes
    N2 General-purpose 2–128 0.5–8 GB
    • Cascade Lake
    • Ice Lake
    Yes Yes Yes Yes
    N2D General-purpose 2–224 0.5–8 GB
    • AMD EPYC Rome
    • AMD EPYC Milan
    Yes Yes Yes Yes
    T2D General-purpose 1–60 4 GB
    • AMD EPYC Milan
    No No No Yes
    N1 General-purpose 1–96 0.95–6.5 GB
    • Skylake
    • Broadwell
    • Haswell
    • Sandy Bridge
    • Ivy Bridge
    Yes Yes Yes Yes
    N1 shared-core 0.2–0.5 3.0–3.4 GB
    • Skylake
    • Broadwell
    • Haswell
    • Ivy Bridge
    • Sandy Bridge
    No No Yes Yes
    C2 Compute-optimized 4–60 4 GB
    • Cascade Lake
    No Yes Yes Yes
    C2D Compute-optimized 2–112 4 GB
    • AMD EPYC Milan
    No Yes No Yes
    M1 Memory-optimized megamem 96 14.9 GB
    • Skylake
    No Yes Yes Yes
    M1 Memory-optimized ultramem 40–160 28.3 GB
    • Broadwell E7
    No No Yes Yes
    M2 Memory-optimized ultramem 208–416 28.3 GB
    • Cascade Lake
    No No Yes No
    A2 Accelerator-optimized high-gpu 12–96 7 GB
    • Cascade Lake
    No Yes No Yes
    A2 Accelerator-optimized mega-gpu 96 14 GB
    • Cascade Lake
    No Yes No Yes
    *For E2 VMs, your processor is selected for you.
    E2 VMs support up to 128 GB of memory total.
    N2D standard and high-CPU VMs have up to 224 vCPUs.

    GPUs and VMs

    GPUs are used to accelerate workloads. You can only attach GPUs to VMs using the N1 machine series or the A2 machine series. GPUs are not supported by other machine series.

    VMs with lower numbers of GPUs are limited to a maximum number of vCPUs. In general, a higher number of GPUs lets you create instances with a higher number of vCPUs and memory. For more information, see GPUs on Compute Engine.

    What's next