Fluidstack

Fluidstack is a specialized AI cloud platform designed to provide high-performance GPU infrastructure for the world's most ambitious AI teams, from frontier startups to established enterprises. The platform's core mission is to eliminate the complexities and delays associated with setting up and managing large-scale GPU clusters, allowing researchers and developers to focus solely on model development and innovation. Fluidstack delivers fully managed, dedicated GPU clusters that are benchmarked to achieve over 95% of theoretical performance, ensuring maximum throughput for demanding AI workloads.

Trusted by leading AI labs and companies like poolside, Fluidstack has proven its capability to deploy thousands of GPUs, such as NVIDIA H100s and A100s, within days—a stark contrast to the months-long lead times of traditional hyperscalers. The platform is built on a purpose-built stack, including the Atlas OS for fast provisioning and the Lighthouse monitoring system for proactive issue detection and auto-remediation, guaranteeing high uptime and reliability.

How to use Fluidstack

Getting started with Fluidstack is a streamlined, consultative process designed for serious AI development:

1. Consultation: Begin by contacting Fluidstack's expert team through their website to discuss your specific computational needs, including the required number and type of GPUs, project timeline, and scale.
2. Cluster Design: Fluidstack's engineers will work with you to design a custom, dedicated GPU cluster optimized for your workloads, whether it's for large-scale model training or high-throughput inference.
3. Rapid Deployment: Once the contract is signed, Fluidstack provisions your dedicated cluster. This process is incredibly fast, with deployments of thousands of GPUs possible within 48 hours.
4. Access and Integration: Access your fully managed cluster through standard orchestration tools like SLURM or Kubernetes. Fluidstack handles all the setup, maintenance, and upgrades, allowing for seamless integration into your existing workflow.
5. Ongoing Management: Leverage Fluidstack's 24/7 hands-on support and the Lighthouse monitoring platform. The system automatically detects and resolves issues, while engineers are available with a 15-minute response SLA for any complex problems.

Core Features of Fluidstack

• Dedicated GPU Clusters: Access to the latest GPU architectures, including NVIDIA H100, H200, B200, and GB200, with the ability to scale to over 12,000 GPUs on a single fabric.
• Atlas OS: A proprietary bare-metal operating system for AI infrastructure that enables fast provisioning, smooth orchestration, and total ownership.
• Lighthouse Monitoring: A proactive monitoring and auto-remediation platform that monitors, heals, and optimizes workloads, catching problems before they impact performance.
• Fully Managed Service: End-to-end management of your cluster, including setup, orchestration (SLURM or Kubernetes), maintenance, and upgrades.
• 24/7 Expert Engineering Support: Direct access to real engineers via Slack with a guaranteed 15-minute response time SLA, providing expert answers and hands-on support.
• High Security and Compliance: Infrastructure is single-tenant by default, ensuring full isolation. The platform is compliant with HIPAA, GDPR, ISO27001, and SOC 2 Type I standards.
• Transparent Pricing: No hidden fees, including zero egress or ingress charges, and on-node NVMe storage is included.

Use Cases for Fluidstack

Fluidstack is ideal for organizations with demanding, large-scale AI requirements:

• Research Labs: Enables top researchers to skip infrastructure delays and focus entirely on pushing the boundaries of AI model development.
• Enterprise AI Teams: Provides reliable, high-performance, and compliant clusters for running business-critical AI applications at scale.
• Sovereign AI Initiatives: Offers secure, region-specific deployments with full physical and operational security to build national AI capabilities.
• Financial Services: Powers fast and secure inference, quantitative modeling, and risk analysis workloads.
• AI Startups: As demonstrated by the poolside case study, Fluidstack allows fast-moving startups to deploy large clusters quickly, accelerate time-to-market, and scale efficiently without large upfront capital or long-term commitments.

Advantages of Fluidstack

Fluidstack offers significant advantages over traditional cloud providers:

• Unmatched Speed: Deploy multi-thousand GPU clusters in days, not months.
• Peak Performance: Clusters are fully burned-in and benchmarked to deliver >95% of theoretical performance from day one.
• Operational Simplicity: Frees your team from the complexities of infrastructure management, from hardware setup to Kubernetes configuration.
• Cost-Efficiency: Transparent, all-inclusive pricing without surprise data transfer fees, leading to a more predictable and often lower total cost of ownership.
• Superior Support: Direct, partnership-style support from experienced engineers, not a tiered ticketing system.

Pricing and Plans

Fluidstack offers flexible pricing models tailored to different needs, all with transparent, all-inclusive terms.

• Reserved Clusters: Designed for large-scale training and inference with terms of 30 days or more. Offers discounted rates and guaranteed resources for 256 to 10,000+ GPUs. Pricing is available upon request.
• On-Demand: For flexible scaling needs, allowing you to launch GPU instances in under 5 minutes and scale from 8 to 4,000+ GPUs. Billed per hour.
• Private Cloud: Custom-built, dedicated clusters for complex needs, specific regions, or custom stacks.

Example on-demand hourly rates:

• NVIDIA H200 SXM: $2.30 / GPU / Hour
• NVIDIA H100 SXM: $2.10 / GPU / Hour
• NVIDIA A100 80GB SXM: $1.30 / GPU / Hour

All plans include 24/7 engineering support, a 15-minute response SLA, managed SLURM or K8s, proactive monitoring, and no egress/ingress fees.