Oracle Cloud (GPU) vs Google Cloud (GCP)
A detailed comparison to help you choose between Oracle Cloud (GPU) and Google Cloud (GCP).
Quick Verdict
3.8/5
Oracle Cloud (GPU)
0 reviews
3.9/5
Google Cloud (GCP)
0 reviews
Google Cloud (GCP) is rated higher (3.9 vs 3.8). Oracle Cloud Infrastructure includes an always-free A1 Arm allocation (2 OCPUs + 12 GB RAM since July 2026, halved from 4 OCPUs + 24 GB) and GPU shapes from ~$2/GPU-hour (A10 VM) to $10/GPU-hour (H100/H200) and $14-15 (B200/B300). Known for its data analytics and AI tooling (BigQuery, Vertex AI).
Oracle Cloud (GPU) Free A1 Arm instances with optional GPU | Google Cloud (GCP) Google's cloud — AI/ML and data analytics focus | |
|---|---|---|
| Overview | ||
| Rating | 3.8 (0 reviews) | 3.9 (0 reviews)✓ |
| Pricing model | freemium | pay-as-you-go |
| Starting price | Free tier available | Free tier available |
| Best for | Enterprise and serious training/inference workloads that want bare-metal NVIDIA or AMD GPU clusters at hyperscaler-reliable terms, especially MI300X and A100 value seekers and existing Oracle/database customers | 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. |
| Features | ||
| IPv6 | ✓ | |
| DDoS protection | ||
| Automated backups | ||
| Snapshots | ||
| Managed option | ||
| Bare metal | ||
| GPU available | ||
| S3-compatible | ||
| Hourly billing | ||
| Free tier | ||
| Data-center locations | ||
| Regions | 50+ regions across 28 countries (NA, SA, EU, MEA, APAC) | — |
| Tags | ||
| Tags | free tiergpu availableeu datacenterus datacenterapac datacenterapi accessarm processors | free tierhourly billingipv6gpu availables3 compatibleeu datacenterus datacenterapac datacenterapi accessterraform providerkubernetes supportarm processors |
| Visit Oracle Cloud (GPU) → | Visit Google Cloud (GCP) → | |
Oracle Cloud (GPU)
Pros
- + Broadest accelerator lineup of any hyperscaler: NVIDIA Blackwell/Hopper/Ampere plus AMD MI300X/MI355X, VMs and bare metal
- + Below-AWS/Azure on-demand GPU list pricing (H100 $10/GPU-hr, A100 80GB $4, MI300X $6) with published, checkable rates
- + Supercluster-class networking (up to 3,200 Gb/sec RDMA) and large local NVMe per node for training checkpoints
- + Credit-backed compute SLA and a full cloud stack (storage, K8s, databases, S3-compatible object) in 50+ regions
Cons
- - GPU quota and capacity processes can require sales engagement; 8-GPU node minimums on the best shapes
- - OCI console/IAM complexity and thinner community documentation than AWS/GCP
- - The 'up to 220% cheaper' claim is a dated vendor comparison; neoclouds undercut on some shapes
- - Egress, storage, image licensing and commitment terms add to headline GPU rates; free tier is CPU-only
Google Cloud (GCP)
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
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