Hyperstack Cloud Review: Is This GPU Cloud Worth It?
Finding a GPU cloud that ticks all the boxes is hard. Whether you’re training AI models, rendering high-res images, or dealing with massive data sets you need power, speed, and affordability all in one place. Hyperstack Cloud is a GPU-focused provider that claims enterprise-grade performance at a fraction of the cost of traditional cloud providers. But does it live up to the hype?
Let’s break down pricing and features, performance, and support. If you’re short on time jump to the key takeaways or the overview table. Otherwise, stick around as we dive deep into what Hyperstack Cloud has to offer.
Table of Contents
Key Takeaways
- Specialized for GPUs: Hyperstack is purpose-built for GPU-accelerated workloads, offering enterprise-grade NVIDIA GPUs.
- Affordable Pricing: Up to 75% cheaper than legacy providers like AWS and Azure.
- Eco-Friendly Infrastructure: 100% renewably powered data centers with energy-efficient operations.
- Optimized Performance: Custom-built ecosystem ensures max efficiency for GPU-heavy tasks.
- Human Support Team: Real people provide multi-region support for quick issue resolution.
Hyperstack Cloud Overview
| Feature | Details |
| GPU Models | NVIDIA H100, A100, L40, RTX A6000/A40 |
| Pricing | Starts at $0.35/hour (reservation pricing) |
| Storage Options | NVMe, HDD block, and HDD shared storage |
| Networking | GPU-optimized architecture for high efficiency |
| Sustainability | 100% renewably powered, with free air cooling in sustainable data centers |
| Regions | Europe and North America |
| API | Bespoke, built for handling GPU workload quickly |
| Support | Human support team with multi-region availability |
| Ease of Use | 1-click deployment, pre-configured flavors, and custom configurations |
| Billing | Accurate to the minute; pay only for what you use |
Why Hyperstack Cloud?
- Cheaper: Up to 75% cheaper than Google Cloud, AWS, or Azure.
- Top GPUs: H100 and A100 GPUs.
- Green: 100% renewable energy-powered data centers.
- Easy: 1-click deploy, pre-configured options, clean interface.
- Custom: Build and optimize VMs for your workloads.
- Uptime: 99.982% uptime guaranteed.
- Pay-As-You-Go: Minute billing.
- Dedicated Support: Humans support in multiple regions.
Why You Might Not Want Hyperstack Cloud
- Limited Footprint: Data centers only in Europe and North America.
- No Free Tier: No free trial like some others.
- GPU Only: Limited support for non-GPU workloads.
- Smaller Ecosystem: Optimized for performance, not all the features of the big hyperscalers.
GPU Models and Pricing
Hyperstack provides an impressive lineup of NVIDIA GPUs, from the RTX A6000 to the cutting-edge H100. Here’s the breakdown:
| GPU Model | VRAM (GB) | Max pCPUs per GPU | Max RAM (GB) per GPU | Pricing (Per Hour) | Reservation Pricing |
| NVIDIA H100 SXM 80GB | 80 | 24 | 240 | $3.00 | From $1.90/hour |
| NVIDIA A100 80GB | 80 | 31 | 240 | $1.40 | From $0.98/hour |
| NVIDIA L40 | 48 | 28 | 58 | $1.00 | From $0.70/hour |
| NVIDIA RTX A6000 | 48 | 28 | 58 | $0.50 | From $0.35/hour |
Hyperstack’s pricing beats most legacy cloud providers, thanks to its GPU-optimized ecosystem that eliminates hidden costs.
Infrastructure and Sustainability
Hyperstack’s infrastructure for Cloud GPU services is unique. Their data centers are powered 100% by renewable energy, mostly hydroelectric. They’re located in cooler climates so they can use free air cooling and reduce energy waste. Plus their equipment is 20x more energy efficient than traditional setups.
This sustainability helps the planet and it means cost savings passed on to you.
Networking and Storage
Hyperstack’s network is optimized for GPU workloads. This means faster data transfer and lower latency for things like AI training and rendering. Storage options:
- NVMe: For data-heavy workloads.
- HDD Block and Shared Storage: For less demanding workloads.
User Experience
1-click deploy to a custom API or pre-configure flavors and create custom setups for your needs. Role-based access control and resource callbacks add layers of organization and automation.
The interface is easy to use even if you’re new to GPU cloud services. Plus, accurate billing so you only pay for what you use – down to the minute.
Customer Support
Unlike some providers that use automated systems, Hyperstack’s support team are real humans. Multi-region support so you can get help no matter where you are. They’re responsive and knowledgeable and can help with technical issues or workload optimization.
Top Hyperstack Cloud Alternatives
If you’re looking at other options, here are four more to consider: GMI GPU Cloud, Vast.ai, AWS, and RunPod. Each of these GPU clouds has its own features and use cases for different GPU workloads.
1. GMI GPU Cloud
GMI GPU Cloud stands out with its infrastructure designed for AI and machine learning workloads. Instant access to the latest GPUs like NVIDIA H100 and H200, highly scalable GPU containers, and pre-configured ML frameworks.
Deploy GPU workloads in minutes with its Kubernetes-based cluster management tools. GMI also offers dedicated private cloud instances for sensitive applications. Global data centers mean enterprise-grade GPU acceleration and easy deployment of GPU-accelerated machine learning projects.
2. Vast.ai
Vast.ai is all about flexibility and cost. Rent Nvidia GPU-optimized AMI in real-time with a bidding system that reduces costs for interruptible instances. Vast offers access to powerful NVIDIA GPUs like A100 and H100, with NVLink and InfiniBand for high-speed interconnectivity.
Great for GPU workloads that need a lot of resources like large-scale machine learning or HPC applications. Marketplace model means competitive pricing so you can get high-performance clusters at a lower cost than traditional cloud providers.
3. RunPod
RunPod is for developers who want flexibility in cloud computing. Its cloud supports public and private image repositories so you can fully customize your GPU instances. With H100 and A100 GPUs available, it’s great for workloads from small models to enterprise projects.
RunPod’s cloud dashboard makes deployment easy and cost-effective so you get the best value. It also supports the Nvidia container toolkit so you can use popular ML frameworks and tools like Amazon Elastic Compute Cloud.
4. AWS EC2
EC2 is a more reliable option than Hyperstack Cloud for AI and machine learning workloads. As one of the biggest cloud providers, AWS uses Amazon’s proven computing environment to deliver infrastructure that is robust, scalable, and secure. EC2 gives you access to high-performance GPU instances like the NVIDIA A100 and V100 for intense AI workloads like deep learning and model training.
With AWS you also get a suite of machine learning tools including SageMaker which makes developing and deploying AI models simple. The platform integrates seamlessly with storage, networking, and analytics services so scaling projects is a breeze.
If you need a cloud with lots of GPU options for AI AWS EC2 is the one. It’s got the history and the AI focus.
Final Thoughts on Hyperstack Cloud
Hyperstack Cloud delivers on affordability, performance, and sustainability. Not the most versatile for non-GPU workloads but it excels in its niche. If you need enterprise-grade GPUs without the cost, Hyperstack is worth a try.
Whether you’re into AI training, rendering, or high-performance computing, this has the tools to get the job done fast and cheap.
Ready to give it a shot? Check out Hyperstack Cloud and see if it fits your workflow.
