Google Cloud vs IO.NET
Compare GPU pricing, features, and specifications between Google Cloud and IO.NET cloud providers. Find the best deals for AI training, inference, and ML workloads.
Google Cloud
Provider 1
IO.NET
Provider 2
Comparison Overview
GPU Pricing Comparison
| GPU Model ↑ | Google Cloud Price | IO.NET Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
H100 80GB VRAM • IO.NET | Not Available |  $1.99/hr★ Best | — | |
H100 80GB VRAM • | ||||
H100 PCIe 80GB VRAM • IO.NET | Not Available | $1.70/hr★ Best | — | |
H100 PCIe 80GB VRAM • | ||||
H200 141GB VRAM • IO.NET | Not Available | $2.49/hr★ Best | — | |
H200 141GB VRAM • | ||||
L4 24GB VRAM • Google Cloud |  $0.56/hr★ Best8x GPU | Not Available | — | |
L4 24GB VRAM • | ||||
RTX 4090 24GB VRAM • IO.NET | Not Available | $0.50/hr★ Best | — | |
RTX 4090 24GB VRAM • | ||||
Tesla T4 16GB VRAM • Google Cloud | $0.55/hr★ Best 4x GPU | Not Available | — | |
Tesla T4 16GB VRAM • | ||||
Tesla V100 32GB VRAM • Google Cloud | $2.48/hr★ Best 8x GPU | Not Available | — | |
Tesla V100 32GB VRAM • | ||||
H100 80GB VRAM • IO.NET | Not Available | $1.99/hr★ Best | — | |
H100 80GB VRAM • | ||||
H100 PCIe 80GB VRAM • IO.NET | Not Available | $1.70/hr★ Best | — | |
H100 PCIe 80GB VRAM • | ||||
H200 141GB VRAM • IO.NET | Not Available | $2.49/hr★ Best | — | |
H200 141GB VRAM • | ||||
L4 24GB VRAM • Google Cloud | $0.56/hr★ Best 8x GPU | Not Available | — | |
L4 24GB VRAM • | ||||
RTX 4090 24GB VRAM • IO.NET | Not Available | $0.50/hr★ Best | — | |
RTX 4090 24GB VRAM • | ||||
Tesla T4 16GB VRAM • Google Cloud | $0.55/hr★ Best 4x GPU | Not Available | — | |
Tesla T4 16GB VRAM • | ||||
Tesla V100 32GB VRAM • Google Cloud | $2.48/hr★ Best 8x GPU | Not Available | — | |
Tesla V100 32GB VRAM • | ||||
Features Comparison
Google Cloud
- Compute Engine
Scalable virtual machines with a wide range of machine types, including GPUs.
- Google Kubernetes Engine (GKE)
Managed Kubernetes service for deploying and managing containerized applications.
- Cloud Functions
Event-driven serverless compute platform.
- Cloud Run
Fully managed serverless platform for containerized applications.
- Vertex AI
Unified ML platform for building, deploying, and managing ML models.
- Preemptible VMs
Short-lived compute instances at a significant discount, suitable for fault-tolerant workloads.
IO.NET
- 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
Pros & Cons
Google Cloud
Advantages
- Flexible pricing options, including sustained use discounts
- Strong AI and machine learning tools (Vertex AI)
- Good integration with other Google services
- Cutting-edge Kubernetes implementation (GKE)
Considerations
- Limited availability in some regions compared to AWS
- Complexity in managing resources
- Support can be costly
IO.NET
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
Considerations
- Newer platform compared to established cloud providers
- Decentralized nature may have performance consistency variations
- Primarily crypto-native payment model ($IO tokens)
Compute Services
Google Cloud
Compute Engine
Offers customizable virtual machines running in Google's data centers.
Google Kubernetes Engine (GKE)
Managed Kubernetes service for running containerized applications.
- Automated Kubernetes operations
- Integration with Google Cloud services
Cloud Functions
Serverless compute platform for running code in response to events.
- Automatic scaling and high availability
- Pay only for the compute time consumed
IO.NET
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
Marketplace
Decentralized pool of GPU providers with unified APIs and competitive pricing.
Pricing Options
Google Cloud
On-Demand
Pay for compute capacity per hour or per second, with no long-term commitments.
Sustained Use Discounts
Automatic discounts for running instances for a significant portion of the month.
Committed Use Discounts
Save up to 57% with a 1-year or 3-year commitment to a minimum level of resource usage.
Preemptible VMs
Save up to 80% for fault-tolerant workloads that can be interrupted.
IO.NET
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
Getting Started
Google Cloud
- 1
Create a Google Cloud project
Set up a project in the Google Cloud Console.
- 2
Enable billing
Set up a billing account to pay for resource usage.
- 3
Choose a compute service
Select Compute Engine, GKE, Cloud Functions, or Cloud Run based on your needs.
- 4
Create and configure an instance
Launch a VM instance, configure a Kubernetes cluster, or deploy a function/application.
- 5
Manage resources
Use the Cloud Console, command-line tools, or APIs to manage your resources.
IO.NET
- 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
Support & Global Availability
Google Cloud
Global Regions
40+ regions and 120+ zones worldwide.
Support
Role-based (free), Standard, Enhanced and Premium support plans. Comprehensive documentation, community forums, and training resources.
IO.NET
Global 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
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