FluidStack stands at the forefront of AI and LLM training by providing immediate access to multi-thousand Nvidia GPU clusters, including the latest H100 and H200 models, all fully interconnected with 3.2Tbps InfiniBand. This infrastructure is designed for large-scale training and inference, offering a seamless deployment process that can scale up to 10,000+ GPUs in just two days. With fully managed services that include Slurm and Kubernetes (K8s), FluidStack ensures that your focus remains on building world-class models, while they handle the complexities of infrastructure management.
The platform boasts an impressive 99% uptime, supported by a dedicated team that offers 24/7 support with a 15-minute response time. This level of service is complemented by custom monitoring and proactive debugging, ensuring that your operations run smoothly without interruption. FluidStack's commitment to excellence is evident in their ability to deploy and operate large-scale GPU clusters efficiently, making them a trusted partner for leading AI companies.
In addition to their large-scale GPU clusters, FluidStack also offers on-demand GPU instances that can be launched in under 5 minutes, scaling seamlessly to 100s of GPUs as needed. This flexibility, combined with the ability to save up to 70% on cloud bills compared to hyperscalers, positions FluidStack as a cost-effective solution for AI labs and companies looking to maximize their GPU power without compromising on performance.
FluidStack's infrastructure is not just about providing access to high-performance GPUs; it's about creating an ecosystem that supports the rapid development and deployment of AI models. With features like fully managed Kubernetes or Slurm, 24/7 support, and the ability to scale to 10K+ GPUs, FluidStack is redefining what it means to have a cloud infrastructure tailored for AI and LLM training.
