c4a-highcpu-16 by Google Cloud Platform

c4a-highcpu-16 is a 16 vCPUs, 32 GB RAM server offered by Google Cloud Platform with 16 vCPUs, 32 GiB of memory and 0 GB of storage. The pricing starts at 0.0813 USD per hour.
16 vCPU
32 GiB Memory
Spare SCore
-
(All-cores)
-
(Single-core)

Specifications

Server Metadata

Vendor ID
gcp
Server ID
1765206
Name
c4a-highcpu-16
Description
16 vCPUs, 32 GB RAM
Family
c4a
Hw Virt
-
Status
active
Observed At
2026-09-26T10:06:56.799536Z

Availability

REGION / IDSPOTONDEMAND
Columbus (US) / us-east5
0.1587 USD/h 0.6061 USD/h
Council Bluffs (US) / us-central1
0.2868 USD/h 0.6061 USD/h
The Dalles (US) / us-west1
0.2868 USD/h 0.6061 USD/h
Moncks Corner (US) / us-east1
0.2868 USD/h 0.6061 USD/h
Ashburn (US) / us-east4
0.361 USD/h 0.6061 USD/h
Mumbai (IN) / asia-south1
0.2431 USD/h 0.6303 USD/h
Eemshaven (NL) / europe-west4
0.0813 USD/h 0.6364 USD/h
Stockholm (SE) / europe-north2
0.3818 USD/h 0.6364 USD/h
Queretaro (MX) / northamerica-south1
0.173 USD/h 0.6606 USD/h
Hamina (FI) / europe-north1
0.1567 USD/h 0.6674 USD/h
Toronto (CA) / northamerica-northeast2
0.2787 USD/h 0.6674 USD/h
St. Ghislain (BE) / europe-west1
0.3159 USD/h 0.6674 USD/h
Johannesburg (ZA) / africa-south1
0.3168 USD/h 0.6674 USD/h
Montréal (CA) / northamerica-northeast1
0.3229 USD/h 0.6674 USD/h
Las Vegas (US) / us-west4
0.3468 USD/h 0.6826 USD/h
London (GB) / europe-west2
0.358 USD/h 0.6909 USD/h
Changhua County (TW) / asia-east1
0.2316 USD/h 0.7018 USD/h
Dallas (US) / us-south1
0.2549 USD/h 0.7152 USD/h
Frankfurt (DE) / europe-west3
0.2793 USD/h 0.7152 USD/h
Madrid (ES) / europe-southwest1
0.3361 USD/h 0.7152 USD/h
Los Angeles (US) / us-west2
0.2783 USD/h 0.7286 USD/h
Warsaw (PL) / europe-central2
0.1907 USD/h 0.7333 USD/h
Doha (QA) / me-central1
0.2943 USD/h 0.7364 USD/h
Jurong West (SG) / asia-southeast1
0.4486 USD/h 0.7477 USD/h
Sydney (AU) / australia-southeast1
0.1592 USD/h 0.7577 USD/h
Tokyo (JP) / asia-northeast1
0.3677 USD/h 0.7783 USD/h
Melbourne (AU) / australia-southeast2
0.1655 USD/h 0.7878 USD/h
Zurich (CH) / europe-west6
0.3389 USD/h 0.794 USD/h
Jakarta (ID) / asia-southeast2
0.3257 USD/h 0.815 USD/h
Santiago (CL) / southamerica-west1
0.362 USD/h 0.8667 USD/h
Osasco (BR) / southamerica-east1
0.3847 USD/h 0.9624 USD/h
Dammam (SA) / me-central2
0.4421 USD/h 0.9699 USD/h

Processor

vCPUs
16
CPU Allocation
Dedicated
CPU Architecture
arm64

System Resources and Accelerators

MEMORY
Memory Amount
32 GiB
GPU
GPU Count
0
GPU Memory Min
0 MiB
GPU Memory Total
0 MiB
GPUs
    STORAGE
    Storage Size
    0 GB
    Storages
      NETWORK
      Inbound Traffic
      0 GB/month
      Outbound Traffic
      0 GB/month
      IPv4
      0

      Server Description

      An arm64 compute-optimized instance featuring sixteen dedicated vCPUs and thirty-two gigabytes of memory for scale-out workloads.

      Compute Optimized

      Google Cloud Platform c4a-highcpu-16 is an arm64-based virtual machine instance within the c4a family, configured with 16 dedicated vCPUs and 32.0 GB of RAM. This configuration establishes a memory-to-core ratio of 2.0 GB per vCPU, aligning it with compute-optimized resource profiles. The instance does not include local storage or GPU accelerators, requiring external network-attached storage for data persistence. It also provides zero complimentary public IPv4 addresses. From a cost-efficiency perspective, the arm64 architecture delivers dedicated compute resources with a streamlined memory footprint, making it a viable option for scale-out workloads. Appropriate workloads for this hardware profile include web serving, containerized applications, and compilation tasks that prioritize CPU capacity over memory density.

      Economics

      Average Price per Region

      Prices per Zone

      Lowest Prices

      Alternatives

      Servers of the Same Family

      INSTANCEvCPUsMEMORYGPUs
      c4a-highcpu-1 12 GiB0
      c4a-standard-1 14 GiB0
      c4a-highmem-1 18 GiB0
      c4a-highcpu-2 24 GiB0
      c4a-standard-2 28 GiB0
      c4a-highmem-2 216 GiB0
      c4a-highcpu-4 48 GiB0

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      c4a-highcpu-16 FAQs