N4D family · General Purposex86_64 · Intel/AMD

n4d-highmem-16

The n4d-highmem-16 machine type has 16 vCPUs and 128 GB of memory. Pricing for this instance starts at $0.89 per hour and $649.29 monthly in the us-central1 region.

Updated June 16, 2026
vCPUs
16
Memory
128 GB
Network
Up to 32 Gbps
Storage
Persistent Disk

Save up to $363/mo on every n4d-highmem-16

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All pricing options

us-central1 · USD · monthly = 730 hrs
Prices exclude local taxes
TermHourlyMonthlySavings
On-Demand
$0.8894$649.29 Baseline
1-Year Committed Use Discount (CUD)
$0.5603$409.02 -37%
3-Year Committed Use Discount (CUD)
$0.4003$292.23 -55%
Preemptible / Spot
$0.3923$286.39 -56%
You could save $362.90/mo on this instance with the right pricing model.
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Monthly cost estimator

Estimate your spend based on actual usage.
730 h
1h365h730h (24/7)
1
Estimated monthly
$649.29
730 hrs × $0.8894/hr × 1

Compute

x86_64 · Intel/AMD
vCPUs i16
Memory i128 GB
Physical processorAMD Turin
Nested VirtualizationNot supported
Sole TenantNot supported
GPUNone
Within N4D family
n4d-highcpu-2
2 vCPU
n4d-standard-2
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n4d-highmem-2
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n4d-highmem-4
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n4d-highmem-8
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n4d-highcpu-16
16 vCPU
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n4d-highmem-16
16 vCPU
n4d-highcpu-32
32 vCPU
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32 vCPU
n4d-highcpu-48
48 vCPU
n4d-highmem-32
32 vCPU
n4d-standard-48
48 vCPU
n4d-highcpu-64
64 vCPU
n4d-highmem-48
48 vCPU
n4d-standard-64
64 vCPU
n4d-highcpu-80
80 vCPU
n4d-standard-80
80 vCPU
n4d-highcpu-96
96 vCPU
n4d-highmem-64
64 vCPU
n4d-standard-96
96 vCPU
n4d-highmem-80
80 vCPU
n4d-highmem-96
96 vCPU

Lock in this rate across your fleet — typically save 30–40%

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Networking

Max egress bandwidth32 Gbps
Tier 1 bandwidthN/A
Enhanced networking iYes (gvnic/virtio)
IPv6 supportYes (Dual-stack VPC)

Storage

Max persistent disks128
Max disk size257 TB
Local SSDsNo local SSD

Compare with another instance

vs.
Specn4d-highmem-16n4d-highcpu-2Δ
vCPUs162-87%
Memory128 GB4 GB-97%
Hourly Price$0.8894$0.0715-92%
Monthly Price$649.29$52.17-92%
Cost optimization

GCP recommender alerts can cut this bill ~30-40%.

Connect your GCP account. We'll identify every underutilized n4d.* instance and show exactly where downsizing, cleaning up orphaned disks, or shifting to CUDs saves money — with zero code changes.