BlackSkye View Providers

Introduction

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Conclusion

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Cloud Computing

Top Cloud GPU Providers for AI & ML in 2025

Top Cloud GPU Providers for AI and Machine Learning in 2025.
Alex
June 15, 2025
•
5 min read
Illustration of cloud servers and GPUs, representing AI and machine learning.

When local GPUs reach their limitations, cloud-based solutions become essential for AI practitioners and machine learning enthusiasts. Finding the right cloud GPU provider can significantly impact your ability to run resource-intensive models like Stable Diffusion or train large neural networks efficiently.

Google Colab: The Starting Point

Google Colab remains the most accessible entry point for cloud GPU computing. Its primary advantage is the free tier that provides limited GPU access without any upfront payment. While the free resources are generous compared to alternatives, they come with usage restrictions that can become problematic for intensive workloads.

The paid tier supposedly offers priority access to better GPUs, but the difference isn't always noticeable. Furthermore, hitting usage limits results in a cooling-off period before resources become available again, making it unsuitable for extended training sessions or multiple inference runs.

Paperspace: Flexible Pay-as-You-Go Solution

Paperspace offers a more straightforward approach with its hourly billing model. The platform provides various GPU options ranging from basic to cutting-edge, allowing users to select the appropriate computing power for their specific needs.

The setup process is straightforward: You choose your operating system, select your GPU type (dedicated or virtual), and configure additional specifications.

For short training sessions or occasional inference runs, Paperspace can be extremely cost-effective. Even high-end GPUs remain affordable when used for just a few hours. For longer workloads spanning days, the cumulative cost remains competitive compared to subscription-based alternatives.

Vagon: Creative Software with ML Potential

While Vagon primarily targets creative professionals using software like Blender, Adobe Suite, and game engines, its GPU resources can be repurposed for machine learning tasks with proper configuration.

Vagon operates on a credit-based payment system, which requires careful planning to avoid unexpected shutdowns when credits are depleted. The platform has reportedly improved since earlier iterations when boot times were lengthy and unexpected shutdowns could result in lost work.

Linode: The Versatile Middle Ground

Linode occupies a sweet spot between user-friendly consumer platforms and complex enterprise solutions. More customizable than Paperspace or Vagon but less intimidating than AWS or Google Cloud, Linode offers flexibility for various use cases beyond machine learning.

Its capabilities extend to website hosting, media servers, game servers, development environments, and machine learning workloads.

The platform provides affordable GPU options with the technical depth to configure more sophisticated setups when needed.

Enterprise Cloud Providers: Future-Proof Solutions

For professional applications or potential startups, major cloud providers like AWS, Google Cloud, Microsoft Azure, and IBM Cloud offer unmatched scalability and integration options. While these platforms have steeper learning curves, gaining proficiency with them provides valuable skills for industry positions.

These providers excel when building production-ready applications, requiring enterprise-grade security, needing seamless integration with other cloud services, or planning for massive scale.

Familiarizing yourself with these platforms, even for personal projects, can enhance your professional credentials in data science and machine learning roles.

Conclusion

When Google Colab's limitations become apparent, several cloud GPU alternatives can keep your machine learning projects moving forward. Whether you need hourly access for occasional training, a versatile development environment, or enterprise-scale infrastructure, understanding the available options helps optimize both performance and cost.

BlackSkye provides an innovative alternative to traditional cloud providers by connecting AI practitioners directly with GPU owners through its decentralized marketplace. Their platform enables cost-effective access to computing resources while allowing hardware owners to monetize idle GPU capacity.