The Ultimate Guide to Evaluating and Renting Cloud GPUs

Renting cloud GPUs is an essential step for scaling AI and machine learning projects, offering the computational power needed to train neural networks, analyze large datasets, and run simulations. But with so many options available, how do you choose the one that best meets your needs without breaking the bank?

In this guide, we’ll explore three approaches to renting GPUs. First, renting directly from cloud providers such as AWS, Azure, or GCP. Second, using cloud brokers to gather quotes on your behalf. Finally, we’ll share a novel approach that blends the best features of both methods, offering the flexibility and scalability developers need without the associated headaches.

By the end, you’ll have a clear roadmap for navigating the GPU rental landscape and optimizing your next AI project.

Option 1: Renting Directly from GPU Providers

The most traditional method is going straight to providers like AWS, Azure, or GCP. These platforms allow you to rent GPU instances, such as the NVIDIA A100, H100, or other high-performance options, and scale your resources as needed.

Pros:

Direct control: Access to a range of GPU types (A100, H100, etc.) with the ability to customize configurations.
Instant access: Most major providers offer on-demand rentals with relatively short setup times.
Proven reliability: Platforms like AWS and GCP are industry leaders with strong service records.

Cons:

Complexity: Navigating multiple provider portals can be time-consuming, especially when comparing GPU instance pricing or availability.
Pricing limitations: Without advanced reservation, on-demand instances can be expensive, especially during peak demand.
Resource constraints: Some providers may experience availability bottlenecks, particularly for high-demand GPUs like the H100.

Best for: Developers who are comfortable managing resources manually and don’t mind juggling multiple provider portals.

Option 2: Using a Cloud Broker

Cloud brokers aim to simplify the GPU rental process by acting as intermediaries between you and the providers. Instead of navigating multiple provider portals and comparing GPU options yourself, cloud brokers collect and present tailored quotes based on your requirements.

This process is designed to save time and offers access to a broad network of providers, including lesser-known ones like Crusoe and Lambda. By submitting your workload details—such as GPU type, project duration, and budget—you delegate the task of sourcing and negotiating pricing to the broker.

While this hands-off approach is convenient, it comes with some drawbacks, including delayed turnaround times for quotes and a lack of real-time pricing transparency. Additionally, most brokers charge service fees, and the limited ability to directly interact with the providers may hinder quick decision-making for urgent projects.

Pros:

Convenience: The broker handles much of the legwork, bringing you tailored quotes for GPU rental or cluster needs.
Choice: Quotes from multiple providers give you a broader view of the market.

Cons:

Lack of immediacy: Waiting for brokers to return with quotes can delay urgent projects. Additionally, not being able to interact directly with providers slows the process down further.
Limited insights: Brokers often lack real-time pricing transparency, making it harder to evaluate cost efficiency dynamically.
Potential fees: Most brokers add additional costs, which could outweigh the benefits of using them.

Best for: Teams that prefer a hands-off approach, have flexible project timelines, and don't mind the additional costs.

Option 3: A Novel Approach with Shadeform

For those seeking the best of both worlds—direct access to resources and the hands off simplicity of a broker—Shadeform provides a streamlined alternative. Its platform offers two key services designed to eliminate the challenges of GPU rentals:

On-Demand GPU Rentals: Shadeform’s GPU marketplace consolidates offers from over 15 major providers like Azure, Lambda, Vultr, and Crusoe. You can compare real-time pricing for GPUs such as the A100, H100, or H200, and manage resources across providers through a single interface.
GPU Reservation Service: Shadeform simplifies planning for large-scale GPU cluster and long-term instance needs. Through a single intake form, you submit your requirements (e.g., GPU type, cluster size, duration). Within 24 hours, Shadeform’s network of 15+ providers delivers tailored quotes, giving you access to cost-optimized GPU resources ready for your project.

Pros:

Transparency: Real-time pricing ensures you’re always getting competitive rates.
Flexibility: Switch seamlessly between providers like AWS and Vultr, ensuring cost efficiency and availability.
Efficiency: Tailored quotes for GPU clusters or instances help you plan for large-scale projects with minimal effort.
Automation: Shadeform’s unified platform simplifies resource management and scaling.
High Availability: Shadeform’s unified platform combines the availability of over 15 providers so you can access A100s, H100s, and even the latest NVIDIA Blackwell B200s and GB200s, with minimal lead time.

Cons:

Learning curve: First-time users may need to familiarize themselves with Shadeform’s features.

Best for: Teams looking for a hassle-free, efficient solution for on-demand rentals or advance GPU rental planning.

Example Workflow using Shadeform

1. Assess Your Project Requirements

Before diving into Shadeform’s platform, start by defining your project needs:

Workload Type: Are you training a large model, running inference, or conducting simulations? This determines the GPU power required (e.g., H100 for training or A6000 for lighter tasks).
Duration: Decide whether you need GPUs for short-term experimentation or long-term, large-scale deployments.
Budget: Set a clear budget range for your rental to narrow down options effectively.

2. Use Shadeform’s Marketplace for Real-Time Price Comparisons

Search by GPU Type: Filter results based on GPU models like A100, H100, or H200.
Compare Providers: View real-time pricing and availability from over 15 major providers, including AWS, Lambda, Crusoe, and Vultr.

3. Submit a Reservation Form for Tailored Quotes

For long-term projects or large-scale GPU cluster needs, Shadeform’s reservation service streamlines the process:

Fill Out the Form: Enter the details of your project, such as the type of GPU, node count, and rental duration.
Receive Tailored Quotes: Within 24 hours, Shadeform’s network of providers will deliver customized quotes optimized for your requirements.
Choose the Best Option: Evaluate the proposals based on cost, availability, and service guarantees, and select the provider that best meets your needs.

4. Deploy and Manage Resources Seamlessly

Once you’ve secured your GPU rental, Shadeform’s unified interface helps you deploy and manage resources efficiently:

One-Click Deployment: Set up instances across multiple providers without navigating individual portals.
Switch Providers On-Demand: If a provider experiences downtime or a more cost-effective option becomes available, you can transition seamlessly with minimal disruption.
Track Usage: Monitor costs directly from the dashboard to ensure you stay within budget.

5. Optimize for Cost and Performance

Leverage Shadeform’s tools to continually optimize your GPU resources:

Simple Scaling: Scale your GPU instances up or down based on project demands.
Resource Reallocation: Reassign workloads to alternate providers when pricing or availability changes.
Support and Assistance: Access Shadeform’s dedicated support team for help with troubleshooting or optimizing configurations.

Key Considerations When Renting GPUs

No matter which method you choose, keep these best practices in mind:

Understand Your Workload: Determine whether you need single GPU instances or larger GPU clusters for tasks like model training or inference.
Compare Pricing: Look for services that provide real-time comparisons (e.g., Shadeform’s marketplace) to ensure you stay within budget.
Plan for Scale: If your project requires significant resources, consider advance reservations to guarantee availability and control costs.
Optimize for Cost and Performance: Balance GPU power with budgetary constraints by leveraging price monitoring and switching options.

The Shadeform Difference

Shadeform merges the strengths of direct rentals and cloud brokers, offering developers the tools they need to manage GPU resources effectively. Whether you’re an AI startup needing quick access to GPU instances or an enterprise planning large-scale model training, Shadeform ensures flexibility, cost-efficiency, and simplicity.

Get Started with Shadeform Today

Ready to elevate your AI workloads? With on-demand rentals and simple reservation services for clusters and instances, Shadeform offers the best of both worlds. Sign up for free and see what's possible.

Frequently Asked Questions (FAQ)

1. Are there any hidden fees with Shadeform?

No, Shadeform does not charge additional fees. You pay the same rates as going directly through the provider.

2. How do I know which GPU type is right for my project?

The choice depends on your workload:

For training large AI models, opt for high-performance GPUs like the A100 or H100.
For inference or lighter tasks, a mid-range GPU such as the A6000 may suffice.

3. How does Shadeform’s reservation service work?

Shadeform’s reservation service is simple:

Fill out a single intake form detailing your GPU requirements.
Within 24 hours, Shadeform’s network of 15+ providers delivers tailored quotes.
Choose the best fit for your project and lock in resources.

4. Can I switch providers after starting a rental?

For on-demand instances, yes. Shadeform’s platform allows you to manage resources across multiple providers seamlessly. If another provider offers better pricing or availability, you can switch with minimal disruption.

5. How does Shadeform compare to using AWS or Azure directly?

While AWS and Azure offer reliable on-demand rentals, Shadeform provides:

More competitive pricing with real-time comparisons across multiple providers.
Advance reservation options to secure GPUs for large-scale tasks.
A single interface for managing resources across providers.
Responsive on-call support for our users.

Relevant Blogs

How to Rent GPU Instances and Clusters on Shadeform

When to Use On-Demand vs. Reserved GPU Instances

The Top 5 Clouds for Renting GPUs