All pricing options
us-central1 · USD · monthly = 730 hrs
Prices exclude local taxes
| Term | Hourly | Monthly | Savings |
|---|---|---|---|
On-Demand | $3.8847 | $2835.85 | Baseline |
1-Year Committed Use Discount (CUD) | $2.4473 | $1786.51 | -37% |
3-Year Committed Use Discount (CUD) | $1.7482 | $1276.22 | -55% |
Preemptible / Spot | $1.3194 | $963.13 | -66% |
You could save $1872.71/mo on this instance with the right pricing model.
Find my savings Monthly cost estimator
Estimate your spend based on actual usage.
730 h
1
Estimated monthly
$2835.85
730 hrs × $3.8847/hr × 1
Compute
vCPUs i80
Memory i320 GB
Physical processorIntel Cascade Lake, Intel Ice Lake
Nested VirtualizationNot supported
Sole TenantNot supported
GPUNone
Within N2 family
n2-highcpu-22 vCPU
n2-standard-22 vCPU
n2-highmem-22 vCPU
n2-highcpu-44 vCPU
n2-standard-44 vCPU
n2-highmem-44 vCPU
n2-highcpu-88 vCPU
n2-standard-88 vCPU
n2-highmem-88 vCPU
n2-highcpu-1616 vCPU
n2-standard-1616 vCPU
n2-highmem-1616 vCPU
n2-highcpu-3232 vCPU
n2-standard-3232 vCPU
n2-highcpu-4848 vCPU
n2-highmem-3232 vCPU
n2-highcpu-6464 vCPU
n2-standard-4848 vCPU
n2-highcpu-8080 vCPU
n2-standard-6464 vCPU
n2-highmem-4848 vCPU
n2-highcpu-9696 vCPU
n2-standard-8080 vCPU
n2-highmem-6464 vCPU
n2-standard-9696 vCPU
n2-highmem-8080 vCPU
n2-standard-128128 vCPU
n2-highmem-9696 vCPU
n2-highmem-128128 vCPU
Lock in this rate across your fleet — typically save 30–40%
Connect your Google Cloud account to apply this pricing logic to every running instance automatically.
Networking
Max egress bandwidth32 Gbps
Tier 1 bandwidth100 Gbps
Enhanced networking iYes (gvnic/virtio)
IPv6 supportYes (Dual-stack VPC)
Storage
Max persistent disks128
Max disk size512 TB
Local SSDsSupported (Scratch Disk)
Compare with another instance
vs.
Specn2-standard-80n2-highcpu-2Δ
vCPUs802-97%
Memory320 GB2 GB-99%
Hourly Price$3.8847$0.0717-98%
Monthly Price$2835.85$52.34-98%
Cost optimization
GCP recommender alerts can cut this bill ~30-40%.
Connect your GCP account. We'll identify every underutilized n2.* instance and show exactly where downsizing, cleaning up orphaned disks, or shifting to CUDs saves money — with zero code changes.