Google Cloud (GCP)

Google's cloud — AI/ML and data analytics focus

3.9(0 reviews)pay-as-you-goFounded 2012United States

free tierhourly billingipv6gpu availables3 compatibleeu datacenterus datacenterapac datacenterapi accessterraform providerkubernetes supportarm processors

Integrates with

Terraform IPv6

Known for its data analytics and AI tooling (BigQuery, Vertex AI).

What Google Cloud (GCP) actually is

Compute Engine is Google's IaaS virtual machine service, announced at Google I/O in June 2012, opened to all comers in May 2013, and generally available since December 2013. Around it sits the wider Google Cloud portfolio — GKE, Cloud Run, BigQuery, Vertex AI, Cloud Storage, and the Gemini model family — but this review is about the VM layer, because that's what you're buying when you compare it against Hetzner, Vultr, or Kamatera in /category/vps-providers.

The infrastructure facts are genuinely strong. Google runs 43 cloud regions and 130 zones, each region spanning three or more zones in three or more physical data centers (a few newer regions — Stockholm, Mexico, Osaka, Montreal — are still expanding to that full footprint). The SLA is among the best published anywhere: 99.99% monthly uptime for instances spread across multiple zones in a region, 99.95% for a single memory-optimized instance, 99.9% for a single instance of any other family. Compare that with the single-node SLAs most VPS providers don't publish at all.

Machine families cover the full range: E2 for cost-conscious general work, N2/N2D and the newer N4 for balanced workloads, C3/C4 compute-optimized, M1/M2 memory-optimized, and accelerator-optimized A2/A3 shapes carrying NVIDIA GPUs for ML training. The reference machine for our pricing column is e2-medium — 2 shared vCPU and 4 GB RAM — which runs $0.0335 per hour (about $24.46 per month) in the cheapest regions such as us-central1 and rises to $0.0536 per hour (about $39.13 per month) in the most expensive ones. A more typical web-server shape, the 2 vCPU / 8 GB e2-standard-2, lands around $49 per month on demand in us-central1 before disk, IP, and bandwidth.

We haven't run our own benchmarks against Compute Engine — there are no GCP entries in our /benchmarks dataset — so treat this as editorial judgment: for raw price per vCPU, GCP does not compete with the European VPS specialists, and it is not trying to. You are paying for the network, the managed-service adjacency, and the SLA.

Pricing: what you really pay

Compute Engine bills per second after a one-minute minimum, which is about as granular as cloud billing gets. The discount ladder is where the complexity starts:

Sustained use discounts apply automatically, up to 30% for eligible machine types (N1, N2/N2D, C2, M1/M2, sole-tenant nodes) that run more than a quarter of a billing month. Important caveat: E2 and N4 machines — the ones most small buyers land on — get no sustained use discounts at all.
Committed use discounts (1 or 3 years) save up to 55% on most machine types and up to 70% on memory-optimized ones. On e2-medium, our price tracker shows the cheapest regions dropping from $24.46 per month on demand to $15.41 with a one-year commitment and $11.01 with three years.
Spot VMs offer the largest cuts, up to 91% off on-demand, at the price of preemption with short notice.

Discount types don't stack. On top of compute, expect line items for persistent disk, external IPs, snapshots, OS licenses (Windows Server on e2-medium adds roughly $33 a month, Red Hat about $10), and network egress. Egress is the bill that surprises people: Premium Tier traffic costs $0.12 per GiB after the first GiB, Standard Tier gives you 200 GiB per month free and then charges $0.085 per GiB up to 10 TiB.

Entry cost is genuinely zero for getting started: a $300 trial credit for new customers (Google's own free-tier documentation says 12 months; recent independent checks found 90 days — read the current terms before planning around it) plus an Always Free tier that includes one e2-micro VM in us-east1, us-west1, and us-central1. The trial never auto-charges — resources stop at the end of the trial and are deleted after a 30-day grace period unless you upgrade. Note that budgets in Google Cloud send alerts; they don't stop spending on Compute Engine. Google added real spend caps in 2026, but only for a handful of services like Cloud Run and Gemini, not for VMs.

Human support is a paid product: paid plans start at $29 per month or 3% of spend. The free tier gets you documentation and community support.

Performance & infrastructure

Google's network is the part of the bill you can argue for. Private global backbone, live migration during host maintenance (a genuinely underrated operational feature — your VMs keep running through most hardware maintenance), automatic restart on failure, and per-region price variation of up to 38% so you can trade latency for cost deliberately. The cheapest regions include us-central1 (Iowa), us-east1 (South Carolina), and us-west1 (Oregon); the most expensive include São Paulo and Dammam.

Storage is a separate decision with separate pricing: persistent disks (balanced, SSD, extreme), local SSD for scratch, and Cloud Storage for objects. Storage classes there run from Standard at $0.000027397 per GiB-hour (about $0.020 per GiB-month) down to Archive at $0.000001644 per GiB-hour (about $0.0012 per GiB-month). Snapshots and backups are billed, not included.

Feature surface is what you'd expect from a hyperscaler: custom machine shapes, sole-tenant nodes for compliance, confidential VMs, OS patch management, instance templates, and deep integration with GKE, BigQuery, and Vertex AI. IPv6 is supported on instance interfaces (dual-stack or IPv6-only configurations), and the Cloud Storage XML API interoperates with Amazon S3 tools and signing, so S3-oriented workflows port over. GPUs are available across the accelerator-optimized families.

One more operational point in GCP's favor: the ecosystem around it is deep. Terraform's Google provider is mature, instance templates and managed instance groups make scaling scripted rather than manual, and the console, gcloud CLI, and REST API are all first-class. For teams running infrastructure as code, few providers are as well-tooled. We also like that regional pricing is published per machine type rather than negotiated — you can model a deployment cost before you talk to anyone, which is not true everywhere at the enterprise end of this market.

Where it falls short

Price-performance for plain servers is the honest weakness. If what you need is two VMs and a generous bandwidth allowance, the European VPS providers deliver the same shape for a fraction of the cost with transfer bundled — our Hetzner entries in /benchmarks make the gap concrete. Google prices compute as a platform component, not as a commodity server.

Billing complexity is the second. Between per-second metering, three discount mechanisms that don't combine, per-GiB egress, OS license line items, and regional price variance, forecasting a monthly bill takes a spreadsheet. The DB row's complaint that "sustained use discounts confuse billing" is fair — worse, the discount doesn't even apply to the machine families the entry-level buyer will pick.

Third: spending controls lag the pricing model. Budgets alert but don't cap VM spend, which matters for teams handing console access to juniors. And a compromised account can run up real charges before anyone notices.

Finally, support is monetized. For a solo developer that's fine; for a business running production on GCP, budget $29 per month or 3% of spend from day one.

Who should pick this

Our pick for teams building on Google's data and ML stack. If BigQuery, GKE, Vertex AI, or the Gemini models are central to your product, colocating VMs in the same project and network is worth the premium — the integration cost savings exceed the compute markup. It also suits organizations that need the SLA (99.99% multi-zone), data-residency guarantees in one of 43 regions, or compliance surface (confidential computing, sole-tenancy) that commodity VPS hosts don't offer.

Skip it if your workload is a handful of always-on servers with predictable traffic and you care about the monthly number. A flat-rate VPS plan with bundled terabytes of transfer will beat GCP on cost every time, and you won't miss the discount ladder.

Key takeaways

Hyperscaler VMs since 2013 (announced 2012); 43 regions, 130 zones; SLA of 99.99% multi-zone, 99.9% single-instance
Per-second billing with three non-stacking discounts: automatic sustained use (up to 30%, not on E2/N4), commitments (up to 55–70%), and Spot (up to 91%)
e2-medium (2 shared vCPU / 4 GB) from about $24 per month on demand, $11 per month on a three-year commitment in the cheapest regions
Egress is the catch: $0.12/GiB Premium Tier, $0.085/GiB Standard after 200 GiB free; paid support starts at $29/month
Free entry is real: $300 trial credit plus an Always Free e2-micro VM in three US regions
Best for data/ML-centric teams and SLA-driven workloads; poor value for simple always-on VPS duty

Sources

Pros

Best published SLA set in the comparison: 99.99% multi-zone, 99.9% single-instance
43 regions and 130 zones with per-region price variance you can trade against latency
Per-second billing and three discount levers — Spot up to 91% off, commitments up to 55–70%
Live migration through host maintenance; deep integration with GKE, BigQuery, Vertex AI
Real free entry: $300 trial credit that never auto-charges, plus an Always Free e2-micro VM

Cons

Poor price-performance for plain VMs versus European VPS specialists; no bundled transfer
Egress is expensive ($0.12/GiB Premium) and billed as a separate line item
Sustained use discounts don't apply to E2 and N4 — the families entry buyers choose
Budgets alert but don't cap Compute Engine spend; human support costs from $29/month

Best For

Data- and ML-centric teams already building on BigQuery, GKE, or Vertex AI, and workloads that need a published multi-zone SLA or data residency in one of 43 regions.