The World’s Best Cheap Cloud GPUs

This assessment of cloud GPUs will be an overview of the best cheap cloud GPU services that are out there. Machine learning and AI applications, like the one I’ve been working on recently, are targeted by these GPUs, and because of that, I know what makes a good cloud GPU provider and what doesn’t.

Read on to learn more about the top cheap cloud GPU services!

Our Top Cloud GPUs Recommendations:

  1. OVHcloud

  2. Linode

#1. OVHcloud



They are a cloud provider with over 1.4 million clients worldwide who they serve with Dedicated Servers, Hosted Private Cloud based on VMware®, and Public Cloud based on OpenStack. For almost 20 years, OVHCloud has been a leader in data center administration and design.

They are vertically integrated since they construct their own data centers and servers, own and run their own network, and handle all client maintenance and support.

They offer services from beginning to end.

Additionally, their Power Usage Effectiveness (PUE) rating is among the lowest in the sector. The usage of our innovative liquid cooling technology is one of the primary causes. Warm water emerges from a maze that cold water continuously flows through on the CPU.

As a result, they no longer use traditional air conditioning, which enables them to pass the savings forward to their clients.

They are a provider of pure infrastructure. Your servers will be maintained by them, and they’ll guarantee excellent availability, performance, and connectivity so you can focus on growing your company.


Need a server with great performance at a reasonable price?

Discover the Kimsufi, So you Start, and Rise ranges of their new OVHcloud ECO range servers and select from more than 100 dedicated server configurations.

Starting at just $6.10 per month!


Create cloud instances with 100% assured resources that can be used for a huge variety of purposes.

Experience the fastest parallel processing on our most powerful Public Cloud instances—up to 1,000 times quicker than a CPU.

Start your public cloud journey with shared resource instances that offer reliable performance at a very low cost.

Virtual servers in the public cloud combine guaranteed resources with flexibility. You can quickly obtain root access, CPU, RAM, and storage with no resource over-allocation. Hourly pricing and a variety of services, including the option to expand resources without having to reinstall, are available through OVHcloud Public Cloud.

Your infrastructure can be automated using the OpenStack API.


Get up-to-the-minute status updates, go through their documentation, view product manuals, or speak with an OVHcloud expert.

They have plenty of guides avaliable online as well for any of your questions or concerns regarding using them as your cloud GPU provider

We love the fact they make it so simple!

#2. Linode



Their dedication to the developer community is respected among developers. Linode doesn’t create goods that are similar to what they have already produced.

Their steadfast commitment to transparency is valued by developers. They don’t hide the costs or complexity of products.

Developers welcome our exclusive emphasis on infrastructure. We’ve demonstrated time and time again that a successful business can be created based on the demands of its clients.

Developers rely on Linode as a cloud provider because they offer an alternative to the pricey, complicated, and cutthroat options they now have on the market.


Offering the lowest price with pride performance-oriented cloud computing

Making cloud computing more accessible has been a key component of our aim since 2003. In order to provide the performance you require at a price you’ll love, we’ve optimized our server, hosting, and computing services.

Simple pricing is based on a flat rate rather than consumption. No extra costs. Pay only as you go. Scale up or down without fear and without consequences.

Without compromising on dependability and security, our pricing for equivalent services surpasses that of AWS, Google, and Azure.

Pricing across all data centers worldwide is uniform and based on the USD price list. We don’t charge more for particular regions, in contrast to other cloud computing providers.

Their equipment is designed precisely to provide you with the best bargain for your plan. Additionally, we regularly upgrade our gear while maintaining the same plan pricing, passing the savings along to you.

Every Linode plan comes with free monitoring, unrestricted API access, substantial transfer, Kubernetes on Linode, connectors, plugins, and support.

For a more intelligent multi-cloud strategy, combine other providers with the Linode cloud’s industry-leading price-to-performance. Conserve money while preserving performance and quality.


NVIDIA Quadro RTX 6000 GPU cards with Tensor, Ray Tracing (RT), and CUDA cores are available as Linode GPU Instances.


The support staff goes above and beyond to offer resources and solutions to resolve client issues.

They respond rapidly to client inquiries across a variety of channels (tickets, emails, phone conversations, social media), placing technical precision and honesty at the core of each engagement.

Through a comprehensive training and mentoring program, they enable every team member to feel competent and capable of managing any situation that comes their way.

We adore Linux and use it daily. For customer escalations, projects, and product development, our work environment and the technologies we employ at Linode make it simple to switch between independent, autonomous work and collaboration with colleagues.

Support’s culture and fundamental principles guide all they do, and they look for any chance to enhance their team, procedures, and the business as a whole.




RunPod is on a quest to completely democratize AI. Our initial objective is to make cloud computing accessible to everyone at prices that are very low without compromising usability, experience, or functionality.

Secure Cloud and Community Cloud are the two cloud computing services that RunPod currently offers.

Our reliable partners operate Secure Cloud in T3/T4 data centers. Due to the close relationship between these, there is great reliability, as well as redundancy, security, and quick response times to reduce any downtimes.

RunPod strongly advises using Secure Cloud for any sensitive and business workloads.

Community Cloud offers strength in numbers and global diversity. They can supply peer-to-peer GPU computing, which links individual compute providers to consumers, through our decentralized platform.

They only accept Community Cloud providers by invitation after thoroughly vetting them to ensure that they deliver reliable computing.

Compared to major cloud service providers like AWS or GCP, both alternatives offer costs that are much more affordable.


All charges, including compute and storage per hour invoicing, are made per minute.

How is RunPod billing carried out?

Based on the type of GPU, each pod has an hourly price. For as long as the pod is operating, you get billed for the compute every minute. The cost will be deducted from your RunPod credits.

Your pods will be immediately halted and you will receive an email if you ever run out of credits.

Eventually, if you don’t top off your credit, pods will be shut down.

How is storage billing carried out?

Currently, we charge $0.1 per gigabyte per month for all storage on active pods and $0.2 per gigabyte per month for volume storage on stopped pods.

RunPod want to make sure that active users have enough space to run their workloads because storage is linked to compute servers.

They will never charge users if the host computer is down or inaccessible over the open internet because storage is charged on a per-minute basis.


What exactly is an instance on demand?

Non-interruptible workloads are appropriate for on-demand instances. As long as you have enough money to keep your pod running, you pay the on-demand pricing and are not subject to competition from other customers.

What exactly is a spot instance?

An interruptible instance called a spot instance can typically be rented for a lot less money than an on-demand instance.

Spot instances are excellent for stateless workloads, such as APIs, or for workloads that may be saved to volume storage on a recurring basis. If your spot instance is interrupted, your volume disk is still kept.


RunPod is happy to help! Join their community on discord, message them in our support chat, or send an email to [email protected]!

Very easy to get in contact with and recommend using RunPod as your Cloud GPU provider.

Lambda GPU Cloud



The majority of my work in AI and machine learning is done when I’m a student, but occasionally I have personal projects that call for me to rent a computer that is more advanced than my laptop for school.

Lambda Labs appeals to me since it’s less expensive than renting equipment from Amazon, Google, or Microsoft.


A 4-GPU instance costs an absurdly cheap $1.50 per hour. The strange amount of RAM (11GB) and the Pascal-based GPUs are very clear indicators that we’re most likely dealing with NVIDIA 1080 TIs.

Additionally, the 8-GPU V100 instance costs only $12 per hour, outpacing Amazon by a considerable amount.


The process of starting an instance sign-up was quite simple. I had to provide my SSH keys after logging in because they only support public-key authentication for their instances. After that, I can choose from one of five possibilities by clicking “Launch Instance.”

To my disappointment, the first RTX 6000-based one that I was anxious to try did not succeed in launching the instance.

The 2x/4x RTX 6000 was my next test. same mistake At this point, I speculated that perhaps their RTX 6000 systems were just fully utilized. I attempted the robust 8x V100 they so enthusiastically promoted on their home page, but I received the same issue. The issue persisted when I tried several times during the day and the day after.

Finally, the only option available to me was the Legacy-branded 1080 Ti, which, in all honesty, was too old-fashioned for any of the models I use. That was a little discouraging, but I kept going.


After attempting to create other instances for a day without success (I just believed that perhaps they were inaccessible or something), I made the decision to try their help.

Since it occupies a sizable portion of the screen and frequently interferes with basic dashboard navigation, it is quite simple to locate.

They’ll respond tomorrow, according to the status, as it’s becoming late here. It’s alright. My message is typed.

When I press submit, a loading circle that never ends appears. Again, I try. Still have the same problem.

For how intrusive their help window is, communicating with them is pretty challenging!



Helsinki, Finland, is where DataCrunch was established. Southern Finland is where they house our infrastructure.

They have a direct connection to Germany via the C-Lion1 submarine cable, which links them to continental Europe.

DataCrunch gives you the tools you need to build customized, scalable AI services. Get in contact with them for additional details on how they can assist you with integrating AI into your operations.

Despite providing high-end hardware, they work to keep our prices lower than those of their rivals.

To ensure that your application works as quickly as possible, their servers utilize the most advanced AI accelerators currently on the market.


Pasted image 0

Relatively inexpensive pricing for DataCrunch’s GPU services.

They start at $2.20/hour and go up to $17.60/hour for their on-demand pricing. These go down significantly when you start to lock in 6-month or 2-year subscriptions.


Powering the A100 virtual dedicated servers are:

8 NVidia® A100 80GB GPUs with a total of 6912 CUDA cores and 432 Tensor Cores are possible.

The current NVidia® flagship silicon is unmatched in terms of raw performance for AI operations.

We only use the SXM4 “for NVLINK” module, which provides up to 600GB/s of P2P bandwidth and memory bandwidth exceeding 2TB/s.

AMD EPYC Rome, second generation, up to 192 threads, 3.3GHz boost clock.

This is how the name 8A100.176V is put together: 176 CPU core threads, 8x RTX A100 and virtualized.


Looking For Support?

You can email them at [email protected].

You can also contact them via their live chat option, which is quite useful and has knowledgeable staff helping you with your questions and needs.

Jarvis Labs



We set up all the hardware, software (Cuda, Frameworks), and infrastructure needed for you to train and use your preferred deep learning model.

Through our python API, you may launch GPU/CPU-powered instances directly from your browser.

Use in less than 5 minutes by following these steps:

  1. Register on
  2. Fill out the billing section with payment information, then use recharge wallet to add money.
  3. Click Launch after selecting a machine type.
  4. With a few clicks, you can also Pause, Resume, and Destroy the instances.


Receive discounts of up to 5% for weekly consumption and 10% for monthly usage. During the week or month when an instance is deployed, it cannot be suspended or terminated.

Once the duration has passed, instances will keep running at the discounted rates until you decide to halt or kill them.


The cost of an instance is calculated per minute. A fee is applied for each minute that an instance was active.

What occurs to instances that are paused?

You pay $0.00014 for each GB of storage used each hour.

If the file size is 20 GB, we charge $0.0028 per hour. As long as you have a balance in your account, we keep the data.

What happens if my balance runs out while instances are still running?

Your running instances are automatically paused when your balance is exhausted.


Support is available 24/7.

You can send an email to [email protected] or use the chat feature on our platform to start a conversation.




Enterprise scale GPU-accelerated applications are catered for by CoreWeave, a dedicated cloud service provider.

For compute-intensive use cases like machine learning, VFX rendering, Pixel Streaming, and batch processing, their Kubernetes-native infrastructure is specifically designed and up to 35x quicker and 80% less expensive than legacy cloud providers.

CoreWeave Cloud was specifically designed to offer the greatest performance for each workload.

The infrastructure is built on the most comprehensive collection of high-end NVIDIA GPUs in the market, but everything from their Kubernetes native cloud platform to their networking and server architecture will always beat traditional cloud providers.


Pricing for CoreWeave Cloud GPU instances is extremely flexible and designed to provide you complete control over both configuration and cost.

The a la carte pricing shown below combines the costs of a GPU component, the number of virtual CPUs, and the amount of RAM allotted to create the overall instance cost.

The GPU selected for your workload or Virtual Server is the only variable, keeping things straightforward. CPU and RAM costs are the same per base unit.

A GPU instance must have at least 1 GPU, 1 vCPU, and 2GB of RAM to be considered genuine. The GPU instance configuration must also have at least 40GB of root disk NVMe tier storage when a Virtual Server is deployed.

Plans start at $0.24/hour and max out at $2.21.


Are there “spot” or interruptible instances available?T

They don’t. Their on-demand pricing can be compared to “interruptible pricing for uninterruptible instances.” When their clients spin up instances on CoreWeave Cloud, they can do so with confidence knowing that they will remain theirs until they choose to spin them down once their workloads are finished, thanks to pricing that enables them to scale.


CoreWeave does not have any official live chat or support number to call that we can find.

Instead, they use a contact form where you fill out your information on a form on their website and they will contact you back.

We would like to see a live support chat, but unfortunately this is not the case.




Providing GPU power for high-performance computing, machine learning, rendering, etc. is the main goal of LeaderGPU, a LeaderTelecom initiative. Instead of VPS, they offer bare-metal servers.

The servers are optimized for the software needed for neural network training and machine learning (TensorflowTM, PyTorch, etc.). Users also have the option of installing their own software.

Additionally, Blender, Maya, Octane Render, CFD, and other render projects using these programs as well as other scientific computations are quite popular (ANSYS, Altair, MSC, etc.).

By using cutting-edge GPUs, flexible pricing, and ongoing service enhancements, they aim to make cloud computing as available, effective, and straightforward as possible.


The number of servers available is momentarily restricted.

Although LeaderGPU would like to apologize for any trouble this may have caused, they are virtually out of servers due to the rapidly increasing demand for our GPU capacities.

They would like to inform you of the waiting list’s current status. At the moment, clients who are currently using servers are their first priority.

Although they are making every effort to expand the number of new servers, there is currently a lack of GPU cards in stock at all Dutch vendors


Looking for efficient GPU instances that are simple to set up and use for upcoming calculations? Effective GPU instances with cutting-edge hardware resources are available from LeaderGPU®.

You can complete any computation rapidly with the aid of powerful GPUs.

You can run the following GPU instances here:

  • GeForce® GTX 1080
  • Tesla® P100
  • GeForce® GTX 1080 Ti
  • RTX™ 2080 Ti
  • T4
  • V100

There are between 2 and 8 GPUs available.


They have a ton of information and FAQs if you ever needed help. They also have online technical support and billing support during normal working hours.

We never had any issues with it, and to us it seems like a great support staff when asked a question!



Finding the best GPU server hardware is a difficult task in and of itself. Our proprietary score method, DLPerf (Deep Learning Performance), forecasts hardware performance rankings for typical deep learning tasks.

They aid in the automation and standardization of the assessment and rating of a wide range of hardware platforms from numerous datacenters and suppliers.


Direct comparison shopping is challenging due to the unique interfaces, naming conventions, and price structures of each cloud compute provider. Once you choose one vendor, vendor lock-in further entrenches higher pricing.

With the help of VAST’s search interface, providers of all stripes—from amateurs to Tier 4 data centers—can be fairly compared.

Get set up on a single interface that links you to a VAST marketplace today to start saving 4-6X.


For convenience and predictable cost, use on-demand rentals. Or, by combining spot auction-based pricing with interruptible instances, you can save an additional 50% or more.

Utilizing scriptable filters and sorting options, search the entire market for offers using the command line interface. Launch instances rapidly directly from the CLI, and automate deployment with ease.

Use interruptible instances and auction pricing to reduce costs by an extra 50% or more. Other competing instances are halted while the highest bidding instances operate.


Do you require assistance establishing GPU computing on our efficient infrastructure? Or simply want to talk? is here to help, though!

Give them more information about your project so they can provide a solution that meets your requirements.

Use the Crisp chat box in the lower right corner of their website, chat on discord, or send them an email to communicate.

Concluding Thoughts

If you are looking for a cheap Cloud GPU provider then you’ve come to the right place.

We recommend choosing from either Linode, or OVHcloud as your providers. They are consistent with their services and have great support.

These three Cloud GPU services are what many people rely on for their uses, and we would have to agree with other reviews that are out there!

Check them out if you want to use a GPU that is reliable and safe to use.