Cloud GPU Platforms
A cloud GPU refers to a graphics processing unit (GPU) used for processing tasks that require high computational power over the internet as part of a cloud computing service. +Show More
| Products | Position | Customer satisfaction | |||
|---|---|---|---|---|---|
Google Cloud Platform (GCP) |
Leader
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Satisfactory
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Offers GPU instances can be connected to existing virtual machines (VMs).
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Number of case studies
1k-2k case studies
Company's number of employees
100k-1m employees
Company's social media followers
50m-60m followers
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Microsoft Azure |
Leader
|
Satisfactory
|
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Azure is one of the top 3 public cloud service providers and has on-premises, hybrid, multicloud, and edge capabilities.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Company's number of employees
100k-1m employees
Company's social media followers
30m-40m followers
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Linode |
Leader
|
Satisfactory
|
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Offers on-demand GPUs for image/video processing, machine learning, and scientific computing with parallel computational power.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Number of case studies
10-20 case studies
Company's number of employees
50-100 employees
Company's social media followers
100k-1m followers
Company
Type of company
private
Founding year
2003
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The Jupyter Notebook |
Leader
|
Satisfactory
|
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Jupyter Notebook is an open-source web application designed to allow users to create and share documents that contain live code, equations, visualizations and narrative text.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Company's number of employees
20-30 employees
Company's social media followers
10k-20k followers
Company
Type of company
private
Founding year
2014
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Amazon Web Services (AWS) |
Leader
|
Satisfactory
|
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Amazon EC2 (Elastic Compute Cloud) provides ready-made virtual machine templates that include GPU-enabled instances.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Company's number of employees
100k-1m employees
Company's social media followers
30m-40m followers
Total funding
$5-10bn
# of funding rounds
3
Latest funding date
January 3, 2023
Last funding amount
$5-10bn
Company
Type of company
public
Founding year
1994
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Google Colaboratory |
Challenger
|
Satisfactory
|
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Colab offers a Jupyter Notebook hosting service that is ready to use without any setup, providing complimentary access to computing resources like GPUs and TPUs. It is particularly beneficial for machine learning, data science, and educational purposes.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
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Oracle Cloud Infrastructure (OCI) |
Challenger
|
Satisfactory
|
|
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|
Offers computing infrastructure and software for organizations to build and run a wide range of applications.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Company's number of employees
100k-1m employees
Company's social media followers
9m-10m followers
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Vultr |
Challenger
|
Satisfactory
|
|
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Vultr is on a mission to make high-performance cloud computing easy to use, affordable, and locally accessible for businesses and developers around the world. A favorite with developers, Vultr has served over 1.5 million customers across 185 countries with flexible, scalable, global cloud computing, cloud GPU, bare metal, and cloud storage solutions. Founded by David Aninowsky, and completely bootstrapped, Vultr has become one of the largest cloud computing platforms in the world, without ever raising equity financing. Learn more at www.vultr.com.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Company's number of employees
100-200 employees
Company's social media followers
100k-1m followers
# of funding rounds
1
Latest funding date
February 20, 2014
Company
Type of company
private
Founding year
2014
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Scaleway |
Challenger
|
Satisfactory
|
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The cloud of choice. Build, deploy and scale applications on Europe's most complete cloud ecosystem. From Serverless architecture to Elastic Metal and everything in between. The platform also offers lineup of NVIDIA GPUs, involving P100, H100, L4 and more.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Company's number of employees
400-1k employees
Company's social media followers
20k-30k followers
# of funding rounds
1
Latest funding date
January 8, 2014
Company
Type of company
private
Founding year
1999
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Salad Virtual Kubelets |
Challenger
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Satisfactory
|
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With support for Kubernetes through the Virtual Kubelets, Salad provides access to significant number of GPUs.
Basis for EvaluationWe made these evaluations based on the following parameters; Customer satisfaction
Average rating
Market presence
Company's number of employees
50-100 employees
Company's social media followers
3k-4k followers
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“-”: AIMultiple team has not yet verified that vendor provides the specified feature. AIMultiple team focuses on feature verification for top 10 vendors.
Sources
AIMultiple uses these data sources for ranking solutions and awarding badges in cloud GPU platforms:
Cloud GPU Leaders
According to the weighted combination of 4 metrics
What are cloud GPU
customer satisfaction leaders?
Taking into account the latest metrics outlined below, these are the current cloud GPU customer satisfaction leaders:
Which cloud GPU solution provides the most customer satisfaction?
AIMultiple uses product and service reviews from multiple review platforms in determining customer satisfaction.
While deciding a product's level of customer satisfaction, AIMultiple takes into account its number of reviews, how reviewers rate it and the recency of reviews.
- Number of reviews is important because it is easier to get a small number of high ratings than a high number of them.
- Recency is important as products are always evolving.
- Reviews older than 5 years are not taken into consideration
- older than 12 months have reduced impact in average ratings in line with their date of publishing.
What are cloud GPU
market leaders?
Taking into account the latest metrics outlined below, these are the current cloud GPU market leaders:
Which one has collected the most reviews?
AIMultiple uses multiple datapoints in identifying market leaders:
- Product line revenue (when available)
- Number of reviews
- Number of case studies
- Number and experience of employees
- Social media presence and engagement
What are the most mature cloud GPU platforms?
Which one has the most employees?
Which cloud GPU companies have the most employees?
45 employees work for a typical company in this solution category which is 22 more than the number of employees for a typical company in the average solution category.
In most cases, companies need at least 10 employees to serve other businesses with a proven tech product or service. 40 companies with >10 employees are offering cloud gpu platforms. Top 3 products are developed by companies with a total of 1m employees. The largest company in this domain is Amazonaws with more than 700,000 employees. Amazonaws provides the cloud GPU solution: Amazon Web Services (AWS)
Insights
What are the most common words describing cloud GPU platforms?
This data is collected from customer reviews for all cloud GPU companies. The most positive word describing cloud GPU platforms is “Easy to use” that is used in 1% of the reviews. The most negative one is “Difficult” with which is used in 1% of all the cloud GPU reviews.
What is the average customer size?
According to customer reviews, most common company size for cloud GPU customers is 1-50 Employees. Customers with 1-50 Employees make up 39% of cloud GPU customers. For an average Cloud solution, customers with 1-50 Employees make up 25% of total customers.
Customer Evaluation
These scores are the average scores collected from customer reviews for all cloud GPU platforms. Cloud GPU Platforms are most positively evaluated in terms of "Overall" but falls behind in "Ease of Use".
Where are cloud GPU vendors' HQs located?
Trends
What is the level of interest in cloud GPU platforms?
This category was searched on average for 8.1k times per month on search engines in 2024. This number has decreased to 0 in 2025. If we compare with other cloud solutions, a typical solution was searched 445 times in 2024 and this decreased to 0 in 2025.
Learn more about Cloud GPU Platforms
Cloud Graphics Units (GPUs) are computing resources that are provided as a service through cloud computing platforms. Instead of being physically located on the user's device, cloud GPUs are located in data centers. They are remotely accessible over the internet.
Different types of Cloud GPUs are offered based on performance, memory, and processing capabilities. These range from high-end GPUs for intensive computing tasks to more standard options for moderate workloads, including NVIDIA and AMD GPU models.
Cloud GPUs are commonly used in areas that require high computational power, such as:
- Machine Learning and AI: Perform parallel processing, making them ideal for training complex models on large datasets.
- Data Analysis: The speed of cloud GPUs makes them suitable for big data analytics and processing large streams of incoming data.
- Cryptocurrency Mining: Can be used for cryptocurrency mining since they perform computations simultaneously.
- Graphic Rendering: Useful for tasks that require rendering high-quality graphics, including virtual reality (VR), video editing and computer-aided design (CAD).
Video processing, gaming, scientific simulations, and data analysis are other comen use cases of Cloud GPUs
Here are some of the main benefits cloud GPUs:
- They can be accessed from anywhere in the world.
- You can scale up or down the computing resources based on your specific need or application.
- They reduce hardware costs in several ways including no maintenance costs or no upfront investment.