Fluidstack
Cloud platform delivering rapid, large-scale GPU infrastructure for AI model training and inference, trusted by leading AI labs and enterprises.
Product Overview
What is Fluidstack?
Fluidstack is a specialized cloud platform offering instant access to thousands of high-performance Nvidia GPUs, including H100s and A100s, for demanding AI workloads. Founded in 2017 at Oxford University, Fluidstack serves top AI companies by providing fully managed GPU clusters and on-demand instances, enabling seamless multi-thousand GPU training and inference at exascale scale. The platform emphasizes affordability, operational reliability, and sustainability, with deployments powered by 100% renewable energy in select regions. Users benefit from quick cluster provisioning, expert support, and flexible deployment options, making Fluidstack a preferred choice for organizations building and scaling advanced AI models.
Key Features
Rapid Access to Large-Scale GPU Clusters
Deploy multi-thousand GPU clusters-including the latest Nvidia H100s and A100s-within days for large-scale AI training and inference workloads.
Fully Managed Infrastructure
Clusters are managed end-to-end by Fluidstack’s team, with deployment options on Kubernetes or Slurm, allowing users to focus on model development instead of infrastructure.
Flexible Deployment and Pricing
Choose between on-demand GPU instances or reserved clusters, with competitive pricing and the ability to lock in savings for long-term projects.
Sustainable and Energy-Efficient Operations
Deploy GPU clusters in data centers powered by 100% renewable energy, supporting environmentally conscious AI development.
24/7 Expert Support
Benefit from dedicated support with a 15-minute response time and 99% uptime, ensuring uninterrupted operations for critical workloads.
Use Cases
- Training Large Language Models : AI labs and research teams can train and fine-tune foundation models and LLMs on powerful, scalable GPU clusters.
- Enterprise AI Deployment : Businesses can launch and manage production-grade AI services requiring high reliability and rapid scaling.
- AI Research and Prototyping : Researchers can quickly access GPU resources for experimentation, benchmarking, and developing new AI techniques.
- Rendering and High-Performance Computing : Organizations can leverage Fluidstack’s infrastructure for rendering, simulation, and other compute-intensive tasks beyond AI.
FAQs
Fluidstack Alternatives
FuriosaAI
High-performance, power-efficient AI accelerators designed for scalable inference in data centers, optimized for large language models and multimodal workloads.
Cerebrium
Serverless AI infrastructure platform enabling fast, scalable deployment and management of AI models with optimized performance and cost efficiency.
Not Diamond
AI meta-model router that intelligently selects the optimal large language model (LLM) for each query to maximize quality, reduce cost, and minimize latency.
Inferless
Serverless GPU platform enabling fast, scalable, and cost-efficient deployment of custom machine learning models with automatic autoscaling and low latency.
Predibase
Next-generation AI platform specializing in fine-tuning and deploying open-source small language models with unmatched speed and cost-efficiency.
Unify AI
A platform that streamlines access, comparison, and optimization of large language models through a unified API and dynamic routing.
TokenCounter
Browser-based token counting and cost estimation tool for multiple popular large language models (LLMs).
Cirrascale Cloud Services
High-performance cloud platform delivering scalable GPU-accelerated computing and storage optimized for AI, HPC, and generative workloads.
Analytics of Fluidstack Website
🇺🇸 US: 75.71%
🇬🇧 GB: 1.79%
🇨🇦 CA: 1.75%
🇳🇬 NG: 1.56%
🇳🇱 NL: 1.49%
Others: 17.7%