FluidStack vs Vast.ai
A detailed comparison to help you choose between FluidStack and Vast.ai.
Quick Verdict
3.6/5
FluidStack
0 reviews
3.7/5
Vast.ai
0 reviews
Vast.ai 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. P2P GPU marketplace connecting researchers and developers with spare compute capacity. Offers rented GPUs at lower rates than centralized cloud providers, ideal for ML training, rendering, and batch processing.
FluidStack Enterprise GPU cloud at competitive pricing | Vast.ai Rent GPUs from individuals for 2-10x cheaper compute | |
|---|---|---|
| Overview | ||
| Rating | 3.6 (0 reviews) | 3.7 (0 reviews)✓ |
| Pricing model | usage-based | usage-based |
| Starting price | From $1.3/mo | From $0.03/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 researchers, rendering studios, and budget-conscious teams running checkpointable training, fine-tune, and batch workloads who are willing to vet hosts themselves |
| 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 | Global — distributed hosts |
| Tags | ||
| Tags | hourly billinggpu availableeu datacenterus datacenter | hourly billinggpu availableeu datacenterus datacenterapac datacenter |
| Visit FluidStack → | Visit Vast.ai → | |
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
Vast.ai
Pros
- + Cheapest public GPU-hour rates anywhere; per-second billing with no minimum charge
- + Always-on capacity across 81 GPU types and hosts in 52 countries — no 'capacity coming soon'
- + Interruptible bidding and reserved discounts give real pricing levers per workload
- + Dense, useful search filters: reliability score, DLPerf, network speed, host tier
- + SOC 2 Type II and HIPAA attestations at the platform level, per third-party comparisons
Cons
- - No SLA, no owned datacenters, and no recourse when an independent host disappears
- - Host variance is real: measured ±11.7% throughput spread on identical H100 SXM specs
- - Storage bills continue on stopped instances; bandwidth is host-set and can be expensive
- - Interruptible preemption risk demands checkpointing discipline
- - Verification and reliability-score formulas are only partially disclosed
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