hyperstack GPU Cloud Provider
Hyperstack offers scalable GPU instances tailored for AI and deep learning workloads, featuring high-performance NVIDIA GPUs and flexible deployment options with no long-term commitments.
Provider Overview
| Name | hyperstack |
| Total Instances | 7 |
| Minimum Price | $0.50/hr |
| Maximum VRAM | 80 GB |
| Available GPU Models |
Hyperstack offers scalable GPU instances tailored for AI and deep learning workloads, featuring high-performance NVIDIA GPUs and flexible deployment options with no long-term commitments.
Get Started with hyperstack
Ready to rent GPUs from hyperstack? Sign up now to explore available instances and start your AI workloads.
Visit Provider Website →About the Provider
Available Instances
| Accelerator | Price/Hour | VRAM | Type | Action |
|---|---|---|---|---|
| H100 SXM | $3.00 | 80 GB | Hopper | View GPU → |
| H100 PCIe NVLink | $1.95 | 80 GB | Hopper | View GPU → |
| H100 PCIe | $1.90 | 80 GB | Hopper | View GPU → |
| A100 PCIe NVLink | $1.40 | 80 GB | Ampere | View GPU → |
| A100 PCIe | $1.35 | 80 GB | Ampere | View GPU → |
| L40 | $1.00 | 48 GB | Ada Lovelace | View GPU → |
| RTX A6000 | $0.50 | 48 GB | Ampere | View GPU → |
Available GPUs
Explore GPU specifications and compare pricing for hyperstack
Compare with Other Providers
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Related Resources
Compute Capability
Check CUDA compute capability and AI feature support for different GPUs
View Reference →About hyperstack GPU Cloud
hyperstack is a leading GPU cloud provider offering 7 instances across 7 different GPU models. With pricing starting at $0.50/hour, they provide competitive options for AI training, inference, and high-performance computing workloads.
Their infrastructure spans 1 regions, making it easy to deploy GPU instances close to your users or data sources. The provider supports popular NVIDIA GPUs including A100 PCIe, A100 PCIe NVLink, H100 PCIe, enabling a wide range of AI/ML applications from deep learning training to real-time inference.
When choosing hyperstack for your GPU cloud needs, consider factors like pricing, regional availability, and supported GPU models. Their platform integrates with popular ML frameworks like PyTorch, TensorFlow, and JAX, making it straightforward to migrate existing workloads or start new projects.
For cost optimization, compare hyperstack's pricing with other providers using our cost estimator tool. Many users find that hyperstack offers competitive rates for long-running training jobs or high-throughput inference workloads, especially when utilizing their spot or preemptible instance options.
External Resources
Learn more about GPUs from these authoritative sources:
Official CUDA programming guide
NVIDIA GPU Specifications →Official NVIDIA GPU specs
TechPowerUp GPU Database →Comprehensive GPU specifications
CUDA Compute Capability Guide →GPU compute capability reference
Ready to Get Started?
Visit hyperstack's website to create an account and start using their GPU instances.
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