FluidStack

FluidStack provides access to the latest generation of NVIDIA hardware, including H100, H200, B200, and GB200 GPUs. These units are fully validated for performance and are available in large-scale dedicated clusters to support intensive AI training and inference tasks.

Yes, we offer high-performance InfiniBand interconnects designed for low-latency communication between nodes. This infrastructure is backed by a 99% uptime SLA at both the node and network levels, ensuring your distributed training jobs run efficiently without bottlenecks.

FluidStack excels at rapid deployment, capable of spinning up multi-thousand GPU clusters within days. In many cases, we can have your large-scale infrastructure ready for production workloads in as little as 48 hours.

No, FluidStack provides fully managed clusters where we handle the zero-setup deployment of orchestration tools like Slurm or Kubernetes. Our team manages all ongoing maintenance and upgrades, allowing your researchers to focus entirely on their AI models.

Yes, we offer a flexible model that includes both on-demand GPU access for burst workloads and reserved capacity for long-term projects. This allows AI companies to scale their infrastructure costs based on their specific development lifecycle and budget.

Absolutely. Because we provide standard Kubernetes or Slurm environments on NVIDIA hardware, our infrastructure is fully compatible with all major frameworks including PyTorch, TensorFlow, and JAX, as well as standard containerization tools like Docker.

By aggregating underutilized capacity from a global network of partner data centers, FluidStack is able to offer high-end GPU compute at significantly more competitive prices than traditional hyperscale providers. This makes large-scale AI training more accessible and cost-effective.

FluidStack focuses on transparent pricing for our dedicated clusters. Because our clusters are fully managed and include proactive monitoring and rapid deployment within the service agreement, you can avoid the complex overhead costs often associated with self-managed cloud infrastructure.

We provide single-tenant isolation at the hardware, network, and storage levels. Unlike many hyperscale providers, we do not use shared clusters, which eliminates 'noisy neighbor' issues and ensures your sensitive AI models and data remain completely private.

Our Secure Ops framework includes comprehensive audit logs and strictly controlled access for FluidStack engineers. This ensures that any maintenance or support activity is fully transparent and restricted to authorized personnel only.

We provide 24/7 engineering support via dedicated Slack channels with a guaranteed 15-minute response SLA. Our team proactively monitors all cluster components to identify and resolve potential hardware or software issues before they impact your workflow.

FluidStack offers a robust 99% uptime SLA covering both individual compute nodes and the InfiniBand networking fabric. This guarantee ensures that your long-running training jobs have the reliability required for enterprise-grade AI development.