FluidStack vs Lambda Labs Comparison
Detailed comparison of features, pricing, and capabilities
Last updated May 1, 2026
Overview
Compare key metrics and features at a glance
FluidStack
https://www.fluidstack.io
FluidStack is a cloud GPU infrastructure provider that aggregates underutilized GPU capacity from data centers worldwide to offer on-demand and reserved GPU compute at competitive prices. The platform enables AI companies, researchers, and developers to access large-scale GPU clusters for training and inference workloads, including support for high-performance interconnects like InfiniBand. FluidStack differentiates itself by sourcing capacity from a distributed network of partner data centers, providing cost-effective alternatives to hyperscale cloud providers for AI/ML workloads.
Lambda Labs
https://lambdalabs.com
Lambda Labs (also known as Lambda) is a cloud computing and hardware company specializing in GPU-based infrastructure for AI and machine learning workloads. The company offers on-demand and reserved GPU cloud instances, as well as on-premise GPU servers and workstations, designed for training and deploying deep learning models. Lambda serves researchers, startups, and enterprises seeking high-performance compute at competitive pricing compared to hyperscale cloud providers.
Quick Comparison
| Detail | FluidStack | Lambda Labs |
|---|---|---|
| Category | AI Cloud Infrastructure | AI Cloud Infrastructure |
| Starting Price | Contact Sales | $496.8/mo |
| Plans Available | 1 | 9 |
| Features Tracked | 16 | 15 |
| Founded | 2019 | 2012 |
| Headquarters | London, United Kingdom | San Francisco, USA |
Features
Detailed feature-by-feature comparison
Feature Comparison
| Feature | | |
|---|---|---|
| api | ||
| API Monitoring | ||
| core | ||
| 1-Click Clusters | ||
| Bare Metal Instances | ||
| Block Storage | ||
| Dedicated GPU Clusters | ||
| Fully Managed Clusters | ||
| GPU Instances | ||
| H100/H200/B200/GB200 Support | ||
| InfiniBand Interconnects | ||
| Kubernetes Support | ||
| Lambda Stack | ||
| Low-Latency Inference | ||
| NVIDIA InfiniBand | ||
| No Egress Fees | ||
| Pay by the Minute | ||
| Private Cloud | ||
| Rapid Deployment | ||
| Slurm Support | ||
| Superclusters | ||
| Transparent Pricing | ||
| Zero Throttling | ||
| custom | ||
| Custom Data Centers | ||
| integration | ||
| Distributed Data Access | ||
| security | ||
| Biometric Access | ||
| Secure Access Controls | ||
| Single-Tenant Clusters | ||
| Single-Tenant Isolation | ||
| support | ||
| 15-Minute Response SLA | ||
| 99% Uptime SLA | ||
| Dashboard Monitoring | ||
| Proactive Monitoring | ||
Pricing
Compare pricing plans and value for money
FluidStack
Contact Sales
Best For
AI companies and researchers needing rapid, cost-effective, fully managed large-scale dedicated GPU clusters for training without hyperscaler lock-in.
Lambda Labs
From $496.8/mo
Price Components
- GPU Hour: $9.86/hour
- Reserved Capacity: $0/cluster
- GPU Hour: $6.16/hour
- GPU Hour: $6.69/hour
- GPU Hour: $3.99/hour
Best For
ML researchers and startups running large-scale distributed training jobs who prioritize cost efficiency and hardware control over managed service breadth.
Integrations
See which third-party services are supported
Supported Integrations
Coming Soon
Integration comparison data for FluidStack, Lambda Labs is being collected and will be available soon.
Strengths & Limitations
Key strengths and limitations of each service
FluidStack
AI companies and researchers needing rapid, cost-effective, fully managed large-scale dedicated GPU clusters for training without hyperscaler lock-in.
- Rapid deployment of multi-thousand GPU clusters in as little as 48 hours with zero-setup management.
- Single-tenant isolation at hardware, network, and storage levels eliminates noisy neighbors unlike hyperscalers.
- Supports latest NVIDIA H100/H200/B200/GB200 GPUs with InfiniBand and 99% uptime SLA.
- 24/7 engineering support via Slack with 15-minute response times and proactive monitoring.
- Enterprise-only pricing requires contacting sales, lacking transparent pay-as-you-go rates.
- Small team of 11-50 employees and seed funding may limit scalability versus larger competitors.
- Aggregated capacity from partner data centers could introduce variability in global availability.
Lambda Labs
ML researchers and startups running large-scale distributed training jobs who prioritize cost efficiency and hardware control over managed service breadth.
- Per-second billing with no egress fees undercuts hyperscale providers on total cost of ownership for GPU workloads
- Bare metal access and Quantum-2 InfiniBand networking enable efficient distributed training across hundreds of GPUs
- Lambda Stack pre-installation eliminates environment setup friction, reducing time-to-training from days to minutes
- Smaller scale and regional availability compared to AWS, Google Cloud, and Azure limits enterprise multi-region deployments
- Limited managed services ecosystem; users handle more infrastructure complexity than with hyperscale competitors
Company Info
Company details and background
FluidStack
Lambda Labs
Comparison FAQ
Common questions about comparing FluidStack and Lambda Labs
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