About FluidStack
FluidStack is a distributed GPU cloud provider that aggregates computing capacity from data centers worldwide to offer affordable GPU instances for AI and machine learning workloads. Founded with the mission of democratizing access to GPU computing, FluidStack connects underutilized GPU resources into a unified platform.
FluidStack stands out through its distributed model, which allows it to offer pricing significantly below traditional cloud providers. By sourcing GPUs from multiple data center partners, FluidStack maintains a diverse inventory including NVIDIA H100, A100, RTX 4090, and other popular accelerators.
The platform is designed for developers and researchers who need cost-effective GPU access without long-term commitments. FluidStack provides API-first infrastructure with simple deployment workflows, making it easy to spin up GPU instances for training, fine-tuning, and inference workloads.
FluidStack Pricing
FluidStack offers competitive pricing across their GPU lineup:
• H100 80GB: From $2.50/hour
• A100 80GB: From $1.80/hour
• RTX 4090: From $0.40/hour
• A10G: From $0.35/hour
• L40S: From $1.50/hour
Pricing varies based on availability and data center location. Volume discounts available for large deployments. No minimum commitment required.
Key Features
Distributed GPU Network
Access GPUs from multiple data centers worldwide for better availability and pricing
API-First Platform
Full REST API for programmatic instance management and automation
Flexible Instance Types
Choose from on-demand, spot, and reserved instances based on your needs
Pre-configured Images
Ready-to-use images with PyTorch, TensorFlow, and other ML frameworks
Multi-GPU Support
Scale up to multi-GPU configurations for distributed training
Persistent Storage
Attach persistent volumes to preserve data across sessions
Best Use Cases
- ✓LLM Fine-Tuning - Affordable H100 and A100 instances for model customization
- ✓Image Generation - RTX 4090 instances for Stable Diffusion and similar models
- ✓ML Training - Cost-effective GPU clusters for research and development
- ✓Inference Workloads - Deploy models at scale with competitive pricing
- ✓Batch Processing - Process large datasets with on-demand GPU power
- ✓Prototyping - Spin up instances quickly for experimentation
Compare Providers
| Provider | Price (A100) | GPUs | Regions | Best For |
|---|---|---|---|---|
| RunPod | $2.75/hr (A100) | 200+ | 31 | Reliability and community |
| Vast.ai | $2.20/hr (A100) | 500+ | 40+ | Lowest prices |
| Lambda Labs | $2.89/hr (A100) | 17+ | 3 | ML-optimized stack |
Frequently Asked Questions
Is FluidStack reliable for production workloads?
FluidStack is suitable for training and batch workloads. For mission-critical production inference, consider providers with SLA guarantees like CoreWeave or Lambda Labs.
How does FluidStack pricing compare to AWS?
FluidStack is typically 40-60% cheaper than AWS EC2 GPU instances. The savings come from their distributed model and lower overhead.