runpod GPU Cloud Provider
RunPod provides affordable and scalable GPU instances for AI and ML workloads, offering both secure cloud and community-hosted options with rapid deployment and serverless capabilities.
Provider Overview
| Name | runpod |
| Total Instances | 14 |
| Minimum Price | $0.36/hr |
| Maximum VRAM | 94 GB |
| Available GPU Models |
RunPod provides affordable and scalable GPU instances for AI and ML workloads, offering both secure cloud and community-hosted options with rapid deployment and serverless capabilities.
Get Started with runpod
Ready to rent GPUs from runpod? Click below to explore available instances and pricing.
Start on RunPod →About the Provider
Available Instances
| Accelerator | Price/Hour | VRAM | Type | Action |
|---|---|---|---|---|
| H100 | $2.79 | 94 GB | Hopper | View GPU → |
| H100 | $2.39 | 80 GB | Hopper | View GPU → |
| H100 | $2.99 | 80 GB | Hopper | View GPU → |
| A100 | $1.64 | 80 GB | Ampere | View GPU → |
| A100 | $1.89 | 80 GB | Ampere | View GPU → |
| A40 | $0.44 | 48 GB | Ampere | View GPU → |
| L40 | $0.99 | 48 GB | Ada Lovelace | View GPU → |
| L40 | $0.86 | 48 GB | Ada Lovelace | View GPU → |
| RTX 6000 Ada | $0.76 | 48 GB | Ampere | View GPU → |
| RTX 6000 Ada | $0.77 | 48 GB | Ada Lovelace | View GPU → |
| A5000 | $0.36 | 24 GB | Ampere | View GPU → |
| RTX 4090 | $0.69 | 24 GB | Ada Lovelace | View GPU → |
| RTX 3090 | $0.43 | 24 GB | Ampere | View GPU → |
| L4 | $0.43 | 24 GB | Ada Lovelace | View GPU → |
Available GPUs
Explore GPU specifications and compare pricing for runpod
Compare with Other Providers
Explore alternative GPU cloud providers and compare pricing
Related Resources
Compute Capability
Check CUDA compute capability and AI feature support for different GPUs
View Reference →About runpod GPU Cloud
runpod is a leading GPU cloud provider offering 14 instances across 9 different GPU models. With pricing starting at $0.36/hour, they provide competitive options for AI training, inference, and high-performance computing workloads.
Their infrastructure spans 2 regions, making it easy to deploy GPU instances close to your users or data sources. The provider supports popular NVIDIA GPUs including A100, A40, A5000, enabling a wide range of AI/ML applications from deep learning training to real-time inference.
When choosing runpod 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 runpod's pricing with other providers using our cost estimator tool. Many users find that runpod 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 runpod's website to create an account and start using their GPU instances.
Visit runpod →