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FluidStack vs Oracle Cloud (GPU)

A detailed comparison to help you choose between FluidStack and Oracle Cloud (GPU).

Quick Verdict

3.6/5

FluidStack

0 reviews

3.8/5

Oracle Cloud (GPU)

0 reviews

Oracle Cloud (GPU) is rated higher (3.8 vs 3.6). FluidStack aggregates GPU capacity from multiple providers to offer H100, A100, and consumer GPU instances. Pay-as-you-go and reserved capacity. EU and US datacenters with competitive pricing. 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).

FluidStack

FluidStack

Enterprise GPU cloud at competitive pricing

Oracle Cloud (GPU)

Oracle Cloud (GPU)

Free A1 Arm instances with optional GPU

Overview
Rating3.6 (0 reviews)3.8 (0 reviews)✓
Pricing modelusage-basedfreemium
Starting priceFrom $1.3/moFree tier available✓
Best forAI labs and platform teams committing to 8-10k+ GPUs for training or heavy inference who want managed Slurm/Kubernetes, per-GPU-hour transparency, and a hands-on infrastructure partnerEnterprise 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
Features
IPv6
DDoS protection
Automated backups
Snapshots
Managed option
Bare metal
GPU available
S3-compatible
Hourly billing
Free tier✓
Data-center locations
Regions
Canada, Netherlands, Norway, Sweden
50+ regions across 28 countries (NA, SA, EU, MEA, APAC)
Tags
Tags
hourly billinggpu availableeu datacenterus datacenter
free tiergpu availableeu datacenterus datacenterapac datacenterapi accessarm processors
Visit FluidStack →Visit Oracle Cloud (GPU) →

FluidStack

Pros

  • + Published per-GPU-hour rate card with no egress or ingress fees
  • + Fully managed Slurm and Kubernetes on bare metal with 24/7 engineering support
  • + Scales from 8 GPUs on-demand to 10k+ reserved — cluster sizes most clouds cannot match quickly
  • + EU capacity in the Netherlands and Nordics for data-residency-sensitive training
  • + Engineering response times measured in hours by SemiAnalysis during ClusterMAX testing

Cons

  • - Aggregated third-party capacity means hardware and day-one polish vary by deployment
  • - Contract-first commercial model — 8-GPU on-demand floor, 256-GPU reserved floor, no free tier
  • - No public uptime SLA, datacenter list, or documentation library
  • - Reactive software supply chain security — unpatched NVIDIA container toolkit found at cluster handover in evaluation
  • - Track record is short relative to the scale of its recent customer commitments
View full FluidStackreview →

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
View full Oracle Cloud (GPU)review →

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