Google Compute Engine Machine Type n2-highcpu-2

General-purpose Google Compute Engine machine type n2-highcpu-2 with 2 vCPU and 2 GB memory. Available in 40 Google Cloud regions.

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Google Cloud VM n2-highcpu-2

Technical facts about the Google Compute Engine machine type n2-highcpu-2.

Series N2
Family General-purpose
vCPU 2
Memory 2 GB
CPU Manufactur Intel
CPU Platform
  • Intel Ice Lake
  • Intel Cascade Lake
CPU Base Frequency 2.6 GHz
CPU Turbo Frequency 3.4 GHz
CPU Max. Turbo Frequency 3.5 GHz
EEMBC CoreMark Benchmark (?) 34740
EEMBC CoreMark Standard Deviation 0.53 %
EEMBC CoreMark Sample Count 3688
SAP Standard Benchmark (?) -
Network Bandwidth 10 Gbps
Network Tier 1 -
Max. Disk Size 257 TB
Max. Number of Disks 128
Local SSD ✔️ Optional
SAP Application ❌
SAP HANA ❌
Spot Provisioning Mode (Spot VM) ✔️
Sustained Use Discount (SUD) ✔️
GCE API Description 2 vCPUs 2 GB RAM

Costs (Pricing) for n2-highcpu-2

Cost and pricing across all regions for Google Cloud VM n2-highcpu-2.

Price per Hour

Min. Avg. Max.
Standard price per hour 0.0717 0.0874 0.1147
Spot provisioning model (Spot VM) 0.0078 0.0221 0.0386

Price per Month

Min. Avg. Max.
Price per month with sustained use discount (SUD) 41.88 51.06 67.01
Spot provisioning model (Spot VM) 5.66 16.13 28.15
1 year commitment (CUD) 32.97 40.11 52.76
3 year commitment (CUD) 23.55 28.65 37.68

Operating System Licenses Costs

Monthly costs for paid premium operating system licenses for Google Compute Engine machine type n2-highcpu-2.

Operating System Month 1Y CUD 3Y CUD
Microsoft Windows Server 67.16
SUSE Linux Enterprise Server 80.3
Red Hat Enterprise Linux 21.02 21.02 21.02
SUSE Linux Enterprise Server for SAP 124.1 50.01 44.72
Red Hat Enterprise Linux for SAP 32.85 32.85 32.85

Price per Region

Costs and pricing for Google Compute Engine machine type n2-highcpu-2 in Google Cloud regions in which the VM is available. Between the most expensive and the cheapest region is a price difference of 37%.

Region Location #Zones #Platf. Hour Spot Month 1Y CUD 3Y CUD
us-central1 Iowa 🍃 5 2 0.0717 0.0195 41.88 32.97 23.55
us-east1 South Carolina 4 2 0.0717 0.0195 41.88 32.97 23.55
us-east5 Columbus 3 2 0.0717 0.0206 41.88 32.97 23.55
us-west1 Oregon 🍃 3 2 0.0717 0.0195 41.88 32.97 23.55
europe-north1 Finland 🍃 3 2 0.0789 0.0242 46.11 36.3 25.93
europe-west1 Belgium 🍃 3 2 0.0789 0.0094 46.07 36.27 25.91
europe-west4 Netherlands 🍃 3 2 0.0789 0.0274 46.11 36.3 25.93
me-west1 Tel Aviv 3 2 0.0789 0.0245 46.07 36.27 25.91
northamerica-northeast1 Montréal 🍃 3 2 0.0789 0.0221 46.11 36.3 25.93
northamerica-northeast2 Toronto 🍃 3 2 0.0789 0.0079 46.11 36.3 25.93
us-west4 Las Vegas 3 2 0.0807 0.0274 47.17 35.28 25.2
us-east4 Northern Virginia 3 2 0.0808 0.0171 47.17 35.28 25.2
asia-east1 Taiwan 3 2 0.083 0.0218 48.49 38.18 27.27
europe-west8 Milan 3 2 0.0832 0.0117 48.58 38.25 27.32
europe-west9 Paris 🍃 3 2 0.0832 0.0224 48.58 38.25 27.32
europe-southwest1 Madrid 🍃 3 2 0.0846 0.0161 49.42 38.91 27.79
us-south1 Dallas 🍃 3 2 0.0846 0.0231 49.42 38.91 27.79
asia-south1 Mumbai 3 2 0.0861 0.0203 50.3 39.6 28.29
asia-south2 Delhi 3 2 0.0861 0.0078 50.3 39.6 28.29
us-west2 Los Angeles 3 2 0.0861 0.0231 50.31 39.61 28.29
us-west3 Salt Lake City 3 2 0.0861 0.0287 50.31 39.61 28.29
australia-southeast2 Melbourne 3 2 0.0865 0.0271 50.51 39.79 28.42
europe-central2 Warsaw 3 2 0.0868 0.0222 50.68 39.9 28.5
me-central1 Doha 3 2 0.0871 0.0276 50.89 40.06 28.62
asia-southeast1 Singapore 3 2 0.0885 0.0316 51.67 40.67 29.05
asia-northeast1 Tokyo 3 2 0.0921 0.0219 53.78 42.34 30.25
asia-northeast2 Osaka 3 2 0.0921 0.0243 53.78 42.34 30.25
asia-northeast3 Seoul 3 2 0.0921 0.0283 53.78 42.34 30.25
europe-west10 Berlin 🍃 3 2 0.0924 0.0202 53.96 42.44 30.32
europe-west2 London 🍃 3 2 0.0924 0.0129 53.96 42.44 30.32
europe-west3 Frankfurt 🍃 3 2 0.0924 0.0267 53.96 42.44 30.32
europe-west12 Turin 3 2 0.0925 0.0182 54.03 42.53 30.38
africa-south1 Johannesburg 3 2 0.0938 0.017 54.78 43.13 30.81
europe-west6 Zurich 🍃 3 2 0.0939 0.025 54.86 43.2 30.85
asia-southeast2 Jakarta 3 2 0.0964 0.0386 56.32 44.33 31.67
asia-east2 Hong Kong 3 2 0.1003 0.0365 58.6 46.13 32.95
australia-southeast1 Sydney 3 2 0.1017 0.0268 59.43 46.81 33.43
southamerica-west1 Santiago 🍃 3 2 0.1025 0.0228 59.89 47.15 33.68
southamerica-east1 São Paulo 🍃 3 2 0.1138 0.0273 66.48 52.35 37.39
me-central2 Dammam 3 2 0.1147 0.0143 67.01 52.76 37.68