FluidStack provides on-demand access to thousands of NVIDIA A100 and H100 GPUs, enabling AI engineers to rapidly scale their training and inference workloads without long-term contracts. The platform offers fully managed GPU clusters with 24/7 support, significantly reducing operational overhead and accelerating model deployment.
Funding
$4.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
AI engineers often face challenges in accessing and scaling GPU resources for training and inference workloads, leading to delays and increased operational overhead. Securing immediate access to high-demand GPUs, such as NVIDIA A100 and H100, can be difficult and expensive, especially without long-term contracts. Managing complex infrastructure, including installation and maintenance of the training stack, further diverts resources from core AI development.
Solution
FluidStack provides on-demand access to a large inventory of NVIDIA GPUs, including A100, H100, and H200, enabling AI engineers to rapidly scale their workloads. The platform offers fully managed GPU clusters with 24/7 support, reducing operational overhead and accelerating model deployment. FluidStack allows users to launch GPU instances in under 5 minutes and scale to hundreds of GPUs on-demand, or reserve large-scale GPU clusters for extended periods. By handling the complexities of infrastructure management, FluidStack enables AI labs to focus on model training and development.
Target Audience
The primary target audience includes AI engineers, AI labs, and enterprises requiring scalable GPU resources for AI training and inference.
Features
- Instant access to thousands of NVIDIA A100, H100, and H200 GPUs
- On-demand GPU instances that can be launched in under 5 minutes
- Fully managed Kubernetes or Slurm clusters with 24/7 support and 99% uptime
- Support for scaling to 10,000+ GPUs
- Best-in-class support with 15-minute response times
- Pre-configured clusters tailored to specific workflows
- Volume discounts for GPU clusters starting at 8+ GPUs