IO.NET
Decentralized GPU network for AI development
io.net is a decentralized GPU network offering H100 (PCIe/SXM) and other GPUs via marketplace pricing, with significant cost differences vs hyperscalers.
Available GPUs
Hourly on-demand pricing. Click column headers to sort.
Prices last updated: April 6, 2026
Pros & Cons
Advantages
- Up to 90% cost savings compared to AWS, GCP, and Azure
- Fastest deployment time in the industry (under 90 seconds)
- Massive global network with 300,000+ GPUs available
- No waitlists, approvals, or long-term contracts required
- Built on proven Ray.io framework used by OpenAI
- Wide range of GPU types from consumer to enterprise grade
- Auto-scaling and dynamic resource allocation
Limitations
- Newer platform compared to established cloud providers
- Decentralized nature may have performance consistency variations
- Primarily crypto-native payment model ($IO tokens)
- Less comprehensive documentation compared to major cloud providers
- Performance depends on distributed node quality and connectivity
Key Features
Massive Decentralized Network
Access to 300,000+ verified GPUs from 139 countries with 6,000+ cluster-ready GPUs
Rapid Deployment
Deploy clusters in under 90 seconds with auto-scaling capabilities
Multiple Deployment Options
Choose from containers, Ray clusters, or bare metal based on workload needs
Built on Ray.io
Uses the same distributed computing framework that OpenAI used to train GPT-3
IO Intelligence
AI models, smart agents, and API integration for workflow automation
Mesh VPN Security
Kernel-level VPN with secure mesh protocols for data protection
Flexible Pricing
Pay with $IO tokens, no long-term contracts or complex KYC requirements
Compute Services
IO Cloud
On-demand GPU clusters for AI/ML workloads with multiple deployment options
IO Intelligence
AI models, smart agents, and API integration platform
- Custom AI model deployment
- Intelligent agent framework
- Easy API integration for workflows
- Automated decision-making capabilities
Marketplace
Decentralized pool of GPU providers with unified APIs and competitive pricing.
Pricing Options
| Option | Details |
|---|---|
| Ray Cluster Pricing | Most cost-effective option for distributed ML workloads using Ray framework |
| Container Pricing | Standard containerized deployments with Docker support |
| Bare Metal Pricing | Premium pricing for direct hardware access and maximum performance |
| Auto-scaling | Dynamic pricing based on actual resource usage with automatic scaling |
Availability & Support
Regions
Global distributed network across 139 countries with intelligent geographic clustering and latency optimization
Support
Documentation portal, Discord community (500,000+ members), Telegram support, and direct engineering support for GPU and driver questions
Getting Started
- 1
Sign up for IO.NET
Create an account on the IO.NET platform with no complex KYC requirements
- 2
Acquire $IO tokens
Purchase $IO tokens for compute payments or add other supported payment methods
- 3
Choose deployment type
Select from containers, Ray clusters, or bare metal based on your workload
- 4
Configure cluster
Specify GPU requirements, region preferences, and scaling options
- 5
Deploy in seconds
Launch your cluster in under 90 seconds and start your AI/ML workloads
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