FluidStack vs RunPod
A detailed comparison to help you choose between FluidStack and RunPod.
Quick Verdict
3.6/5
FluidStack
0 reviews
3.7/5
RunPod
0 reviews
RunPod is rated higher (3.7 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. RunPod is a GPU cloud marketplace with community and secure cloud options. Deploy Docker containers on RTX, A100, and H100 GPUs. Serverless inference endpoints and network volumes for persistent storage.
FluidStack Enterprise GPU cloud at competitive pricing | RunPod Community GPU cloud with on-demand pods | |
|---|---|---|
| Overview | ||
| Rating | 3.6 (0 reviews) | 3.7 (0 reviews)✓ |
| Pricing model | usage-based | usage-based |
| Starting price | From $1.3/mo | From $0.27/mo✓ |
| Best for | AI 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 partner | ML developers and small teams running training, fine-tuning or bursty inference who want cheap per-second GPU access without an enterprise contract |
| 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 | — |
| Tags | ||
| Tags | hourly billinggpu availableeu datacenterus datacenter | hourly billinggpu availableeu datacenterus datacenter |
| Visit FluidStack → | Visit RunPod → | |
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
RunPod
Pros
- + Published per-second GPU pricing from $0.27/hr with no commitment
- + Free egress and cheap network volumes at $0.07/GB/month for the first TB
- + Secure Cloud tier with SOC 2 Type II and a 99.9% uptime SLA
- + Serverless endpoints scale to zero for spiky inference workloads
- + S3-compatible API over network volumes for data movement without booting pods
Cons
- - Community Cloud reliability depends on vetted third-party hosts with no SLA
- - Idle volume disk bills at double the running rate and uncovered volumes can be deleted
- - Support is thin; no named-engineer escalation on standard accounts
- - No published IPv6 or DDoS protection position for pods
- - No free tier and no general-purpose cloud services alongside the GPUs
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