What is the difference between Google Cloud and TensorDock?

Google Cloud and TensorDock 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 TensorDock?

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 TensorDock?

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

Google Cloud vs TensorDock LLM API Pricing 2026

LLM API Pricing Comparison

Total models: 8Both available: 0Google Cloud: 8TensorDock: 0

Showing 8 of 8 models

Prices per 1M tokens · Last updated: 7/28/2026, 2:13:52 AM

Model ↑	Google Cloud	TensorDock	Input Diff ↕
Gemini 3 Flash Google	$0.500 in $3.00 out	Not available	—
Gemini 3 Pro Google	$2.00 in $12.00 out	Not available	—
Gemini 3.1 Flash Image Google	$0.500 in $3.00 out	Not available	—
Gemini 3.1 Flash Lite Google	$0.250 in $1.50 out	Not available	—
Gemini 3.1 Pro Google	$2.00 in $12.00 out	Not available	—
Gemini 3.5 Flash Google	$1.50 in $9.00 out	Not available	—
Gemini 3.5 Flash-Lite Google	$0.300 in $2.50 out	Not available	—
Gemini 3.6 Flash Google	$1.50 in $7.50 out	Not available	—

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.

TensorDock

KVM Virtualization
Root access and dedicated GPUs with full OS control, manage your own drivers and Windows 10 support
Global Distribution
100+ locations across 20+ countries with enterprise-grade servers in tier 3/4 data centers
Pay-per-second Billing
Continuous billing with automatic server deletion when balance reaches zero
API Integration
Well-documented REST API for programmatic server management with metadata and availability

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

TensorDock

Advantages

Up to 80% cheaper than hyperscalers with competitive marketplace pricing
Wide GPU selection with 45 different models from RTX 4090 to H100 SXM5
No quotas, hidden fees, or long-term commitments required
99.99% uptime standard with vetted hosts and quality hardware

Considerations

Marketplace model means pricing varies by host and location
Newer platform compared to established cloud providers
Dependent on independent host quality and availability

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

TensorDock

CPU Cloud

High-performance CPU instances with latest Intel Xeon and AMD EPYC processors

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.

TensorDock

Pay-as-you-go

Per-second billing with automatic server deletion when balance reaches zero

Reserved Pricing

Long-term rental options available for enterprise customers

Marketplace Pricing

Independent hosts compete and set their own pricing for best market rates

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.

TensorDock

Get Started

1
Sign Up
Register in just two clicks with email or GitHub account
2
Deposit Funds
Start with as little as $5 deposit for pay-as-you-go billing
3
Deploy a GPU
Run your workload on enterprise-grade hardware in 30 seconds

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.

TensorDock

Global Regions

100+ locations across 20+ countries with enterprise-grade servers in tier 3/4 data centers

Support

24/7 staff availability with 24-hour response time standard, Discord community, comprehensive documentation