Google Compute Engine Machine Type n2d-highcpu-16

General-purpose Google Compute Engine machine type n2d-highcpu-16 with 16 vCPU and 16 GB memory. Available in 40 Google Cloud regions.

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Google Cloud VM n2d-highcpu-16

Technical facts about the Google Compute Engine machine type n2d-highcpu-16.

Series N2D
Family General-purpose
vCPU 16
Memory 16 GB
CPU Manufactur AMD
CPU Platform
  • AMD Rome
  • AMD Milan
CPU Base Frequency 2.45 GHz
CPU Turbo Frequency 2.8 GHz
CPU Max. Turbo Frequency 3.5 GHz
EEMBC CoreMark Benchmark (?) 327122
EEMBC CoreMark Standard Deviation 1.22 %
EEMBC CoreMark Sample Count 628
SAP Standard Benchmark (?) -
Network Bandwidth 32 Gbps
Network Tier 1 -
Max. Disk Size 257 TB
Max. Number of Disks 128
Local SSD ✔️
SAP Application ❌
SAP HANA ❌
Spot Provisioning Mode (Spot VM) ✔️
Sustained Use Discount (SUD) ✔️
GCE API Description 16 vCPUs 16 GB RAM

Costs (Pricing) for n2d-highcpu-16

Cost and pricing across all regions for Google Cloud VM n2d-highcpu-16.

Price per Hour

Min. Avg. Max.
Standard price per hour 0.3293 0.6069 0.7984
Spot provisioning model (Spot VM) 0.0579 0.1309 0.257

Price per Month

Min. Avg. Max.
Price per month with sustained use discount (SUD) 192.38 354.51 466.39
Spot provisioning model (Spot VM) 42.27 95.58 187.63
1 year commitment (CUD) 151.47 278.44 367.18
3 year commitment (CUD) 108.19 198.89 262.29

Operating System Licenses Costs

Monthly costs for paid premium operating system licenses for Google Compute Engine machine type n2d-highcpu-16.

Operating System Month 1Y CUD 3Y CUD
Microsoft Windows Server 537.28
SUSE Linux Enterprise Server 80.3
Red Hat Enterprise Linux 126.14 126.14 126.14
SUSE Linux Enterprise Server for SAP 299.3 119.94 107.75
Red Hat Enterprise Linux for SAP 189.8 189.8 189.8

Price per Region

Costs and pricing for Google Compute Engine machine type n2d-highcpu-16 in Google Cloud regions in which the VM is available. Between the most expensive and the cheapest region is a price difference of 59%.

Region Location #Zones #Platf. Hour Spot Month 1Y CUD 3Y CUD
asia-south1 Mumbai 3 2 0.3293 0.112 192.38 151.47 108.19
us-central1 Iowa 🍃 5 2 0.499 0.1039 291.49 229.49 163.93
us-east1 South Carolina 4 2 0.499 0.1039 291.49 229.49 163.93
us-east5 Columbus 3 2 0.499 0.061 291.49 229.49 163.93
us-west1 Oregon 🍃 3 2 0.499 0.1039 291.49 229.49 163.93
europe-west1 Belgium 🍃 3 2 0.5489 0.1932 320.65 252.44 180.32
me-west1 Tel Aviv 3 2 0.5489 0.0933 320.64 252.44 180.32
europe-north1 Finland 🍃 3 2 0.5494 0.1045 320.94 252.65 180.47
europe-west4 Netherlands 🍃 3 2 0.5494 0.0898 320.92 252.65 180.47
northamerica-northeast1 Montréal 🍃 3 2 0.5494 0.2197 320.92 252.65 180.44
northamerica-northeast2 Toronto 🍃 3 2 0.5494 0.1136 320.92 252.65 180.44
us-east4 Northern Virginia 3 2 0.562 0.1378 328.31 245.56 175.4
us-west4 Las Vegas 3 2 0.562 0.1557 328.31 245.56 175.4
asia-east1 Taiwan 3 2 0.5778 0.2312 337.51 265.72 189.81
europe-west8 Milan 3 2 0.5788 0.0633 338.13 266.21 190.16
europe-west9 Paris 🍃 3 2 0.5788 0.136 338.13 266.21 190.16
europe-southwest1 Madrid 🍃 3 2 0.5888 0.1487 343.96 270.8 193.44
us-south1 Dallas 🍃 2 2 0.5888 0.0956 343.96 270.8 193.44
asia-south2 Delhi 3 2 0.5994 0.0989 350.12 275.61 196.88
us-west2 Los Angeles 3 2 0.5994 0.1691 350.12 275.65 196.9
us-west3 Salt Lake City 3 2 0.5994 0.1387 350.12 275.65 196.9
australia-southeast2 Melbourne 2 2 0.6019 0.1629 351.58 276.91 197.79
me-central1 Doha 3 2 0.6063 0.0874 354.16 278.83 199.17
asia-southeast1 Singapore 3 2 0.6156 0.1096 359.61 283.09 202.22
asia-northeast1 Tokyo 3 2 0.6408 0.1688 374.35 294.71 210.51
asia-northeast2 Osaka 3 2 0.6408 0.0784 374.34 294.71 210.51
asia-northeast3 Seoul 3 2 0.6408 0.1047 374.34 294.71 210.51
europe-central2 Warsaw 3 2 0.6429 0.1974 375.56 295.4 211
europe-west2 London 🍃 3 2 0.6429 0.1662 375.56 295.4 211
europe-west3 Frankfurt 🍃 3 2 0.6429 0.257 375.56 295.4 211
europe-west12 Turin 3 2 0.6437 0.0579 376.03 296.04 211.47
africa-south1 Johannesburg 3 2 0.6527 0.106 381.27 300.17 214.42
asia-southeast2 Jakarta 3 2 0.671 0.1219 391.97 308.57 220.42
europe-west6 Zurich 🍃 2 2 0.6981 0.1606 407.77 321.02 229.33
asia-east2 Hong Kong 3 2 0.6982 0.1448 407.86 321.11 229.35
australia-southeast1 Sydney 3 2 0.7081 0.2012 413.62 325.78 232.7
southamerica-west1 Santiago 🍃 2 2 0.7136 0.0954 416.84 328.17 234.42
europe-west10 Berlin 🍃 3 2 0.7685 0.1245 448.9 353.41 252.45
southamerica-east1 São Paulo 🍃 3 2 0.7921 0.1281 462.72 364.38 260.27
me-central2 Dammam 3 2 0.7984 0.0906 466.39 367.18 262.29