A Detailed Look at GPU Rentals from puzl.cloud and GPU Mart

Compare the top GPU rental providers to find the perfect match for your AI research needs. Dive into detailed specifications and reviews to make an informed decision.

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Features

Delve into the features of GPU rental companies.
Explore their adaptibility, pricing models, integration, and customer support features and find the best fit for you.

puzl.cloud

GPU Mart

Platforms Supported
Windows
Mac
Linux
SaaS/Web
On-Premises
iPhone
iPad
Android
Chromebook
Platforms Supported
Windows
Mac
Linux
SaaS/Web
On-Premises
iPhone
iPad
Android
Chromebook
Audience

Puzl Cloud caters to programmers, researchers, and enterprises requiring flexible, budget-friendly cloud services for artificial intelligence, data science, and intensive computational tasks.

Audience

GPU Mart targets developers, researchers, and businesses needing high-performance GPU resources for AI, deep learning, 3D rendering, and large-scale parallel tasks

Support
Phone Support
24/7 Live Support
Online
Support
Phone Support
24/7 Live Support
Online
API
Offers API
API
Offers API
Pricing
$0.26 per hour
Free Version
Free Trial
Pricing
$0.09 per hour
Free Version
Free Trial
Pricing Plans Conclusion
  • Puzl.cloud's Flexible and Cost-Effective Pricing:
    Puzl.cloud offers highly competitive and flexible pricing ideal for a variety of computational needs. The NVIDIA A100 is priced at $1.60 per hour, with fractional options to further reduce costs: $0.80 per hour for half an A100 and $0.40 per hour for a quarter of an A100. Long-term commitments offer substantial discounts, with prices for the A100 dropping to $1.28 per hour for a 6-month commitment and $0.96 per hour for a 3-year commitment. Puzl.cloud also emphasizes zero infrastructure maintenance fees and integrates seamlessly with Kubernetes for efficient workload management.
  • GPU Mart's Versatile and Affordable Pricing:
    GPU Mart provides a range of GPU pricing options designed for various high-performance computing needs. Prices for basic GPUs like the NVIDIA K80 start at $76.30 per month, while high-end GPUs like the NVIDIA A100 are available for $639 per month. GPU Mart also offers options such as the RTX 3060 Ti for $179 per month and the RTX A5000 for $539 per month. The platform includes features like dedicated GPU resources, 24/7 technical support, and scalable options to add or remove computing resources as needed, ensuring flexibility and cost-effectiveness for various applications
Reviews/Ratings
Overall
4.4/5
Ease
4.0/5
Feature
4.5/5
Design
4.0/5
Support
3.5/5
Reviews/Ratings
Overall
4.0/5
Ease
3.5/5
Feature
4.5/5
Design
4.0/5
Support
3.5/5
Training
Documentation
Webinars
Live Online
In Person
Training
Documentation
Webinars
Live Online
In Person
Integrations
Amazon Web Services (AWS)
Brev.dev
Caffe
Dropbox
Google Cloud Platform
Google Drive
Jupyter Notebook
Keras
Microsoft Azure
OpsVerse
Integrations
Amazon Web Services (AWS)
Brev.dev
Caffe
Dropbox
Google Cloud Platform
Google Drive
Jupyter Notebook
Keras
Microsoft Azure
OpsVerse
Summary
  • Puzl.cloud: Ideal for Kubernetes-Based Workflows
    Puzl.cloud stands out for its Kubernetes-native platform and flexible pricing, making it an excellent choice for users needing cost-effective and scalable solutions. The fractional GPU options and significant discounts for long-term commitments make it suitable for a wide range of AI and machine learning projects. The platform’s integration with Kubernetes ensures easy deployment and efficient management of workloads.
  • GPU Mart: Perfect for Cost-Effective and High-Performance Solutions
    GPU Mart excels with its versatile and affordable pricing, offering a variety of GPU options tailored to different needs. This model is ideal for users seeking scalable and cost-effective solutions for applications ranging from AI training to high-performance computing. GPU Mart’s transparent pricing, extensive GPU options, and support for heavy workloads make it a highly competitive choice for developers and teams.

Decentralized 
computing for AGI.

Decentralized computing unlocks AGI potential by leveraging underutilized GPU resources for scalable, 
cost-effective, and accessible research.

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