Google Cloud vs Latitude.sh
Compare GPU pricing, features, and specifications between Google Cloud and Latitude.sh cloud providers. Find the best deals for AI training, inference, and ML workloads.
Google Cloud
Provider 1
Latitude.sh
Provider 2
Comparison Overview
GPU Pricing Comparison
| GPU Model ↑ | Google Cloud Price | Latitude.sh Price | Price Diff ↕ | Sources |
|---|---|---|---|---|
A100 SXM 80GB VRAM • Latitude.sh | Not Available | 8x GPU | — | |
A100 SXM 80GB VRAM • | ||||
A30 24GB VRAM • Latitude.sh | Not Available | 2x GPU | — | |
A30 24GB VRAM • | ||||
GH200 96GB VRAM • Latitude.sh | Not Available | — | ||
GH200 96GB VRAM • | ||||
H100 80GB VRAM • Latitude.sh | Not Available | — | ||
H100 80GB VRAM • | ||||
L4 24GB VRAM • Google Cloud | 8x GPU | Not Available | — | |
L4 24GB VRAM • | ||||
L40 40GB VRAM • Latitude.sh | Not Available | 4x GPU | — | |
L40 40GB VRAM • | ||||
L40S 48GB VRAM • Latitude.sh | Not Available | — | ||
L40S 48GB VRAM • | ||||
RTX 6000 Ada 48GB VRAM • Latitude.sh | Not Available | 8x GPU | — | |
RTX 6000 Ada 48GB VRAM • | ||||
RTX A5000 24GB VRAM • Latitude.sh | Not Available | 8x GPU | — | |
RTX A5000 24GB VRAM • | ||||
RTX A6000 48GB VRAM • Latitude.sh | Not Available | 4x GPU | — | |
RTX A6000 48GB VRAM • | ||||
Tesla T4 16GB VRAM • Google Cloud | 4x GPU | Not Available | — | |
Tesla T4 16GB VRAM • | ||||
Tesla V100 32GB VRAM • Google Cloud | 8x GPU | Not Available | — | |
Tesla V100 32GB VRAM • | ||||
A100 SXM 80GB VRAM • Latitude.sh | Not Available | 8x GPU | — | |
A100 SXM 80GB VRAM • | ||||
A30 24GB VRAM • Latitude.sh | Not Available | 2x GPU | — | |
A30 24GB VRAM • | ||||
GH200 96GB VRAM • Latitude.sh | Not Available | — | ||
GH200 96GB VRAM • | ||||
H100 80GB VRAM • Latitude.sh | Not Available | — | ||
H100 80GB VRAM • | ||||
L4 24GB VRAM • Google Cloud | 8x GPU | Not Available | — | |
L4 24GB VRAM • | ||||
L40 40GB VRAM • Latitude.sh | Not Available | 4x GPU | — | |
L40 40GB VRAM • | ||||
L40S 48GB VRAM • Latitude.sh | Not Available | — | ||
L40S 48GB VRAM • | ||||
RTX 6000 Ada 48GB VRAM • Latitude.sh | Not Available | 8x GPU | — | |
RTX 6000 Ada 48GB VRAM • | ||||
RTX A5000 24GB VRAM • Latitude.sh | Not Available | 8x GPU | — | |
RTX A5000 24GB VRAM • | ||||
RTX A6000 48GB VRAM • Latitude.sh | Not Available | 4x GPU | — | |
RTX A6000 48GB VRAM • | ||||
Tesla T4 16GB VRAM • Google Cloud | 4x GPU | Not Available | — | |
Tesla T4 16GB VRAM • | ||||
Tesla V100 32GB VRAM • Google Cloud | 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.
Latitude.sh
- Automated bare metal
Provision servers with user data, RAID, and SSH over a documented REST API.
- GPU Accelerate fleet
RTX 6000 Ada, H100, and L40S capacity with dual 100 Gbps networking on multi-GPU nodes.
- Global footprint
20 locations spanning the US, Europe, Latin America, and Asia-Pacific.
- Transparent pricing
Hourly and monthly rates published for GPU and CPU bare metal.
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
Latitude.sh
Advantages
- 20-region coverage with instant deploy options in the US, EU, LATAM, and APAC
- GPU nodes ship with dual 100 Gbps fabric, large RAM, and NVMe for AI training
- API-first platform with detailed REST documentation for automation
- Published hourly pricing for both metal and GPU catalogs
Considerations
- GPU catalog is narrower than hyperscalers
- Some regions show limited or unavailable GPU stock depending on plan
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
Latitude.sh
Accelerate GPU Bare Metal
Dedicated GPU servers tuned for AI training and inference.
GPU Virtual Machines
Virtualized GPU plans for quick starts and cost-effective deployment.
Metal Bare Metal
General-purpose dedicated servers with high core counts and NVMe.
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.
Latitude.sh
GPU Bare Metal Hourly
Hourly billing for dedicated GPU servers including RTX 6000 Ada configurations with transparent published pricing.
GPU Virtual Machines
Cost-effective virtualized GPU options with H100 and L40S available in select regions.
CPU Bare Metal Plans
Hourly and monthly billing options for CPU-focused bare metal servers with regional pricing variations.
Transparent Regional Pricing
Published hourly rates for all GPU and CPU plans with pricing that varies by region (US, Brazil, Europe, APAC).
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.
Latitude.sh
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.
Latitude.sh
Global Regions
20 locations across Dallas, Los Angeles, New York, Chicago, Ashburn, Miami, London (2), Frankfurt (2), Amsterdam, Sao Paulo (2), Mexico City, Buenos Aires, Bogota, Santiago, Singapore, Tokyo (2), and Sydney (2).
Support
API reference, contact sales, and a trust center; platform tooling exposes SSH, RAID, and user-data options on provision.
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