The best GPU cloud provider depends on your project needs and personal preferences. Below is a list of some affordable GPU options and their benefits to help you find a platform that fits your budget without compromising performance.
Pricing overview across GPU cloud platforms
| Provider | NVIDIA RTX A6000 $/ GPU-hr | NVIDIA A100 80 GB $/ GPU-hr | NVIDIA H100 80 GB $/ GPU-hr | Free credits / trials |
|---|---|---|---|---|
| Thunder Compute [1] | $0.27 | $0.78 | $1.38 | — |
| AWS [2] | — | $2.74 | $6.88 | 750 hrs t2.micro + startup credits |
| Google Cloud | — | $3.67 | $14.19 | 90-day $300 credit |
| Lambda Labs [3] | $0.92 | $1.48 | $3.44 | — |
| RunPod* [4] | $0.77 | $1.19 | $2.39 | — |
| Hyperstack [5] | $0.50 | $1.39 | $1.90 | — |
| TensorDock [6] | $0.39 | $0.85 | $1.99 | — |
| Vast.ai** [7] | $0.40 | $0.75 | $1.47 | — |
**"Starting from" prices taken from each vendor's public pricing page listed in Sources.*
How to choose between cloud providers
<ul> <li>Budget vs. reliability - Budget GPU cloud providers beat hyperscalers on cost but have less extensive ecosystems of other services, e.g., storage.</li> <li>Ecosystem lock-in - AWS/GCP integrations are handy <em>if you're already there</em>; otherwise outbound data fees bite when you migrate.</li> <li>Billing granularity - Paying per minute (Thunder Compute, RunPod) is about 40% cheaper than hourly for bursty workloads.</li> <li>Scale ceiling - Need 100x A100 tonight? Go Lambda Labs clusters or AWS UltraClusters; smaller clouds have stricter limits.</li> </ul>
1. AWS, GCP, Azure, Oracle (the big guys)
Price highlight - AWS A100 80 GB $2.74/hr, H100 80 GB $6.88/hr
You are likely already familiar with these options. They are often the first names that come to mind when you think about cloud. If you are looking for robust storage solutions, built-in Kubernetes support, and integration with existing cloud infrastructure, one of these is likely your best option.
Additionally, if you work for a startup, these programs have generous credit offerings which can total hundreds of thousands of dollars.
Unfortunately, you pay a price for the complete ecosystem you receive: AWS, GCP, Azure and Oracle are often the most expensive cloud GPU providers, are difficult to set up, and lock you in with data egress costs.
If you don’t have an existing cloud presence and want to get started quickly, it is often best to look elsewhere.
2. Thunder Compute
For an 8-hour fine-tuning run on an A100 80 GB GPU, Thunder Compute costs $6.24 vs. $21.92 on AWS.
Thunder Compute balances the absolute lowest cost (up to 80% lower than AWS or GCP) with simple user experience.
<ul> <li>Focuses on on-demand virtual machines for startups, research, and prototyping. </li> <li>Dedicated A100 hosts in U.S. data-centers.</li> <li>Spin up an on-demand instance in 30 seconds.</li> </ul>
This solution is best suited for developers looking for the best bang for their buck.
Use Thunder Compute's VSCode extension to access a low-cost A100 80 GB GPU in one click.
3. Lambda Labs
Lambda sells a mix of enterprise and on-demand cloud services. Their Lambda On-Demand GPU Cloud provides access to powerful GPU clusters, while also offering colocation services for companies' AI infrastructure. Lambda has carved out a niche providing clusters for large-scale AI projects and excels at projects that require a combination of cloud and on-premises hardware solutions.
Its on-demand instance pricing is higher than some other options on this list, especially for bare metal offerings. Unfortunately, Lambda does not allow you to stop instances without additional charges for persistent storage.
4. TensorDock
TensorDock offers a decentralized marketplace for GPU cloud instances, with costs ~60% lower than larger providers. TensorDock provides a traditional VM-based experience for a fraction of the cost. To achieve this lower cost, TensorDock uses a mix of consumer and older data center GPUs. Additionally, other cloud features like storage buckets are not available.
5. HyperStack
Hyperstackis a high-performance cloud GPU platform built for AI, ML, generative AI and HPC workloads. It offers optimised NVIDIA GPU VMs, high-speed networking, on-demand Kubernetes, object storage and a full-stack Gen AI platform (AI Studio) to help teams train and deploy models faster. With reservation discounts, spot VMs and hibernation, Hyperstack lowers costs without compromising performance. Its NVMe storage enables fast data access, though some GPUs may be temporarily unavailable during peak demand.
6. RunPod
RunPod focuses on providing a seamless user experience for container deployment, similarly to Modal at lower cost. They have optimized infrastructure for low cold start times and auto-scaling capabilities for efficient resource management in production inference scenarios.
Users cite frequent reliability concerns with RunPod GPUs, but this occasionally makes sense for the lower cost. RunPod is a great option for quickly starting and scaling AI apps, however reliability concerns often limit long-term viability for production apps at scale.
7. Modal
Modal focuses on developer experience and has earned an excellent reputation in the developer community. Modal is container-based and focused on scaling apps to production. To deploy to Modal, developers must annotate their Python code to containerize and scale certain functions.
It's built on top of GPUs provided by Oracle Cloud, with support for AWS, GCP, and Azure. The major drawback is cost, Modal is often the most expensive cloud provider on a per-hour basis.
8. Vast.ai
Vast.ai is another low-cost marketplace for renting GPUs. Vast.ai is primarily container-based, although they have begun rolling out support for traditional Virtual Machines.
Similarly to TensorDock, users frequently complain about reliability and setup issues, where instances may randomly disappear.
Conclusion
With dozens of GPU cloud providers on the market, start by matching cost, reliability, and ecosystem fit to your project. When in doubt, pick a cheaper, simpler option - you can always scale up later. If you work for a startup, check out our analysis of Startup-Friendly GPU Cloud Providers for tailored recommendations.
Ready to run your first notebook? -> Launch a Thunder Compute GPU instance and get building.
FAQs about Cloud GPU Providers
Q: Who is the cheapest GPU cloud provider in 2025?
A: Thunder Compute is the cheapest GPU cloud platform, offering reliable A100 80 GB GPUs on-demand for $0.78/hr.
Q: Who has the cheapest cloud GPUs?
A: For consumer hardware, spot marketplaces such as TensorDock can reach a few cents per hour for lighter workloads. For stable on-demand access on top-tier hardware, Thunder Compute's virtualized GPUs are usually the lowest-cost option.
Q: Cheapest cloud GPUs for development?
A: Indie developers and research teams can start with Thunder Compute's RTX A6000 at $0.27/hr or A100 80 GB at $0.78/hr.
Q: How much does a cloud GPU cost per hour?
A: On-demand rates in the table range from $0.27 to $14.19 per GPU-hr depending on model and provider. Thunder Compute's A100 80 GB GPUs are $0.78/hr.
Sources
<ul> <li><a href="https://www.thundercompute.com/pricing">Thunder Compute - Pricing</a></li> <li><a href="https://aws.amazon.com/ec2/instance-types/">AWS - EC2 Instance Types</a></li> <li><a href="https://cloud.google.com/compute/gpus-pricing">Google Cloud - GPU Pricing</a></li> <li><a href="https://lambda.ai/instances">Lambda Labs - GPU Cloud</a></li> <li><a href="https://www.runpod.io/pricing">RunPod - Pricing</a></li> <li><a href="https://www.hyperstack.cloud/gpu-pricing?utm_source=getdeploying.com&utm_content=nvidia-a6000">Hyperstack - GPU Pricing</a></li> <li><a href="https://dashboard.tensordock.com/deploy?_gl=1*1g9yjln*_gcl_au*MTExNTgwMTMyMC4xNzcxODU3MjE0*_ga*NDgxMzI2Mjc4LjE3NzE4NTcyMTQ.*_ga_P5VZBVFLDE*czE3NzE4NTcyMTQkbzEkZzAkdDE3NzE4NTcyMTQkajYwJGwwJGgw">TensorDock - Deploy</a></li> <li><a href="https://cloud.vast.ai/?ref_id=292888&utm_source=getdeploying.com&utm_content=nvidia-a6000">Vast.ai - Cloud</a></li> <li><a href="https://aws.amazon.com/free">AWS - Free Tier</a></li> <li><a href="https://cloud.google.com/free">Google Cloud - Free Tier</a></li> </ul>