What GPU types does Fluidstack offer?

Fluidstack offers various GPU types including . Check the pricing table above for current availability and pricing.

How do I get started with Fluidstack?

Contact expert, Request pricing, Deploy infrastructure

What are Fluidstack's main advantages?

Fluidstack's main advantages include: Purpose-built infrastructure for AI workloads with enterprise partnerships, Large-scale GPU availability with rapid deployment capabilities, Fully managed SLURM or Kubernetes orchestration, No data transfer fees and included local storage, 24/7 engineering support with 15-minute response SLA, Single-tenant infrastructure with no noisy neighbors, Flexible scaling from 8 GPUs to 10,000+ GPU clusters, Performance-tested hardware with 95%+ efficiency guarantee.

What are Fluidstack's limitations?

Fluidstack's main limitations include: Enterprise-focused platform may be complex for small-scale users, Primary focus on AI and ML workloads may not suit general compute needs, Newer player compared to established hyperscale cloud providers, Custom solutions may require longer setup times than self-service options.

Fluidstack

Infrastructure for Abundant Intelligence

Rapidly-catching neocloud🇬🇧 GBbudget

Last reviewed Mar 14, 2026

Leading AI cloud platform providing purpose-built infrastructure for training and inference, partnering with top AI labs, governments, and enterprises.

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Fluidstack does not publish public hourly pricing.

Contact the provider directly for a quote.

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Pros & Cons

Advantages

Purpose-built infrastructure for AI workloads with enterprise partnerships
Large-scale GPU availability with rapid deployment capabilities
Fully managed SLURM or Kubernetes orchestration
No data transfer fees and included local storage
24/7 engineering support with 15-minute response SLA
Single-tenant infrastructure with no noisy neighbors
Flexible scaling from 8 GPUs to 10,000+ GPU clusters
Performance-tested hardware with 95%+ efficiency guarantee

Limitations

Enterprise-focused platform may be complex for small-scale users
Primary focus on AI and ML workloads may not suit general compute needs
Newer player compared to established hyperscale cloud providers
Custom solutions may require longer setup times than self-service options

Key Features

Atlas OS

Bare-metal OS for AI infrastructure with fast provisioning, smooth orchestration, and total ownership

Lighthouse

Monitoring and optimization system that catches problems before they impact workloads

Single-Tenant by Default

Fully isolated infrastructure at hardware, network, and storage levels with no shared clusters

24/7 Engineering Support

Direct engineering support with 15-minute response SLA and secure access controls

No Hidden Fees

No egress or ingress fees, with on-node NVMe storage included

Performance Guarantee

Clusters tested to deliver 95%+ of theoretical performance from day one

Compute Services

GPU Clusters

Dedicated, high-performance GPU clusters that are fully isolated, fully managed, and always available.

Pricing Options

Option	Details
Reserved Clusters	Designed for large-scale training and inference, deployed on fully managed cloud infrastructure. 256-10,000+ GPUs with monthly or annual terms and discounted rates.
On Demand	Launch GPU instances in under 5 minutes and seamlessly scale to 100s of GPUs on-demand. 8-4,000+ GPUs with hourly billing.
Private Cloud	Custom dedicated clusters for complex needs with flexible terms and region-specific deployments.

Getting Started

1
Contact expert
Talk to a Fluidstack expert to discuss your specific AI infrastructure needs
2
Request pricing
Get custom pricing for your GPU cluster requirements
3
Deploy infrastructure
Launch your dedicated GPU cluster with fully managed support