Crusoe vs Vast.ai Comparison
Detailed comparison of features, pricing, and capabilities
Last updated May 1, 2026
Overview
Compare key metrics and features at a glance
Crusoe
https://www.crusoe.ai
Crusoe is an AI cloud infrastructure company that provides purpose-built cloud computing services optimized for AI workloads, including GPU clusters for training and inference. Originally founded as Crusoe Energy Systems, the company pivoted to focus on sustainable AI cloud computing, leveraging stranded and flared natural gas to power data centers, reducing carbon emissions compared to traditional grid-powered facilities. Crusoe offers high-performance computing resources tailored for machine learning, generative AI, and large-scale model training, positioning itself as an environmentally conscious alternative to hyperscale cloud providers.
Vast.ai
https://vast.ai
Vast.ai is a decentralized cloud GPU marketplace that connects individuals and businesses who need GPU compute resources with hosts who have idle GPU hardware available for rent. The platform allows users to rent GPU instances at significantly lower prices than traditional cloud providers by aggregating consumer and data center GPUs from around the world. Vast.ai supports a wide range of use cases including machine learning training, inference, rendering, and other compute-intensive workloads.
Quick Comparison
| Detail | Crusoe | Vast.ai |
|---|---|---|
| Category | AI Cloud Infrastructure | AI Cloud Infrastructure |
| Starting Price | Contact Sales | Contact Sales |
| Plans Available | 5 | 3 |
| Features Tracked | 17 | 16 |
| Founded | 2018 | 2017 |
| Headquarters | San Francisco, USA | San Francisco, USA |
Features
Detailed feature-by-feature comparison
Feature Comparison
| Feature | | |
|---|---|---|
| api | ||
| CLI & SDK | ||
| REST API | ||
| core | ||
| 99.98% Uptime | ||
| AMD Compute | ||
| Accelerated Storage | ||
| Clusters for Training | ||
| Crusoe AutoClusters | ||
| Diverse GPU Support | ||
| Elastic Scaling | ||
| GPU Marketplace | ||
| Instance Filtering | ||
| Interruptible Instances | ||
| Managed Kubernetes | ||
| MemoryAlloy Technology | ||
| NVIDIA GPUs | ||
| On-Demand Instances | ||
| Optimized Networking | ||
| Per-Second Billing | ||
| Pre-Built Templates | ||
| Real-Time Pricing | ||
| Reserved Instances | ||
| Serverless Inference | ||
| Sustainable Energy | ||
| integration | ||
| Git Integration | ||
| JupyterLab Support | ||
| Multi-Cloud Support | ||
| security | ||
| Direct Payload Delivery | ||
| SOC2 Certification | ||
| SSO Support | ||
| VPC Installs | ||
| support | ||
| 24/7 Expert Support | ||
| 24/7 Support | ||
| Cost Tracking | ||
Pricing
Compare pricing plans and value for money
Crusoe
Contact Sales
Price Components
- NVIDIA H200 141GB HGX: $4.29/GPU-hour
- NVIDIA H100 80GB HGX: $3.9/GPU-hour
- NVIDIA A100 80GB SXM: $1.95/GPU-hour
- NVIDIA A100 80GB PCIe: $1.65/GPU-hour
- NVIDIA A100 40GB PCIe: $1.45/GPU-hour
Best For
ESG-focused AI teams training massive LLMs or running inference who prioritize sustainable, high-uptime GPU clusters with auto-failover.
Vast.ai
Contact Sales
Price Components
- GPU Usage: $0/second
- GPU Usage: $0/second
- Reserved Capacity: $0/term
Best For
Cost-sensitive ML practitioners and researchers running batch training, inference, or rendering on flexible, preemptible GPU workloads.
Integrations
See which third-party services are supported
Supported Integrations
Coming Soon
Integration comparison data for Crusoe, Vast.ai is being collected and will be available soon.
Strengths & Limitations
Key strengths and limitations of each service
Crusoe
ESG-focused AI teams training massive LLMs or running inference who prioritize sustainable, high-uptime GPU clusters with auto-failover.
- Powers data centers with flare gas and solar for carbon-negative AI computing, slashing emissions versus grid-reliant hyperscalers.
- MemoryAlloy tech delivers 9.9x faster Time-to-First-Token and 5x inference throughput on NVIDIA H100/A100 GPUs.
- AutoClusters auto-remediate GPU failures for 99.98% uptime in elastic, Kubernetes-managed scaling from notebooks to clusters.
- Spot GPU instances and pay-per-1M-token inference offer cost savings over on-demand hyperscale pricing.
- Smaller scale (201-500 employees, Series C) limits global data center footprint versus hyperscalers like AWS or Azure.
- Reliance on stranded energy sources may constrain capacity expansion and geographic availability.
- Enterprise/reserved pricing for GB200/B200 requires custom sales outreach, lacking self-serve transparency.
Vast.ai
Cost-sensitive ML practitioners and researchers running batch training, inference, or rendering on flexible, preemptible GPU workloads.
- Decentralized marketplace aggregates 20,000+ GPUs worldwide, offering 3-6x savings via dynamic real-time pricing over hyperscalers.
- Per-second billing with on-demand, interruptible (50%+ cheaper), and reserved options for flexible cost control.
- Supports diverse high-end GPUs like RTX 4090, A100, H200 with pre-built AI templates and multi-GPU configs.
- Instant deployment via web, CLI, SDK, API, and native Docker for rapid ML training and inference.
- Interruptible instances risk preemption, unsuitable for production needing guaranteed uptime.
- Decentralized peer-to-peer model may yield inconsistent reliability versus managed hyperscaler infrastructure.
- Small team (11-50 employees) limits enterprise-grade support and scale compared to giants like AWS.
Company Info
Company details and background
Crusoe
Vast.ai
Comparison FAQ
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