What is the difference between Google Cloud and IO.NET?

Google Cloud and IO.NET are both cloud GPU providers offering different pricing models, features, and GPU availability. Use our comparison tool to see real-time pricing and feature differences.

Which is cheaper: Google Cloud or IO.NET?

Pricing varies by GPU model and usage requirements. Check our real-time comparison table to find the best deals for your specific needs.

Can I switch between Google Cloud and IO.NET?

Yes, both providers offer flexible cloud GPU services. However, consider factors like data transfer costs, setup time, and specific features when switching between providers.

How many GPU models are available for comparison?

We track pricing for 2 different GPU models across both Google Cloud and IO.NET, with 0 models available from both providers.

Google Cloud vs IO.NET GPU Cloud Pricing 2026

GPU Pricing Comparison

Total GPUs: 2Both available: 0Google Cloud: 2IO.NET: 0

Showing 2 of 2 GPUs

Last updated: 5/23/2026, 12:38:04 PM

GPU Model ↑	Google Cloud Price	IO.NET Price	Price Diff ↕	Sources
Tesla T4 16GB VRAM • Google Cloud	$0.16/hr★ Best	Not Available	—	Google Cloud
Tesla T4 16GB VRAM • Google Cloud $0.16/hour Updated: 5/17/2026 ★Best Price Not Available Google Cloud
Tesla V100 32GB VRAM • Google Cloud	$1.12/hr★ Best	Not Available	—	Google Cloud
Tesla V100 32GB VRAM • Google Cloud $1.12/hour Updated: 5/17/2026 ★Best Price Not Available Google Cloud

Tesla T4 16GB VRAM • Google Cloud	$0.16/hr★ Best	Not Available	—	Google Cloud
Tesla T4 16GB VRAM • Google Cloud $0.16/hour Updated: 5/17/2026 ★Best Price Not Available Google Cloud
Tesla V100 32GB VRAM • Google Cloud	$1.12/hr★ Best	Not Available	—	Google Cloud
Tesla V100 32GB VRAM • Google Cloud $1.12/hour Updated: 5/17/2026 ★Best Price Not Available Google Cloud

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

Get Started

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

Get 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

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