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RunPod is a globally distributed GPU cloud platform that allows you to develop, train, and scale AI applications efficiently. It offers over 50 template environments, streamlines the training process, and provides serverless endpoints for deploying models to production. With seamless GPU workload management, RunPod minimizes ML ops and maximizes application building.

You can choose from 50+ template environments, including popular frameworks like PyTorch and TensorFlow, or bring your own custom container. RunPod also enables you to select from 30+ regions worldwide, ensuring global interoperability. The platform offers ultra-fast NVMe storage, limitless storage capacity, and easy deployment configuration.

Create production-ready endpoints that autoscale from 0 to 100s of GPUs in seconds and pay only for the resources you use. RunPod eliminates idle GPU costs by charging per second of usage and provides real-time logs and metrics for monitoring and debugging. It prioritizes security and compliance, with enterprise-grade GPUs and lightning-fast cold starts using Flashboot. With its user-friendly interface and efficient workflows, RunPod is the cost-effective solution for GPU rental and AI development.


  • Over 50 template environments for easy development setup
  • Efficient training process with benchmarking capabilities
  • Serverless endpoints for deploying models to production
  • Seamless GPU workload management for minimal ML ops
  • Global interoperability with 30+ regions
  • Ultra-fast NVMe storage and limitless capacity
  • Easy deployment configuration
  • Autoscaling endpoints for efficient resource utilization
  • Charges per second of usage to eliminate idle GPU costs
  • Real-time logs and metrics for monitoring and debugging
  • Enterprise-grade GPUs for security and compliance
  • Lightning-fast cold starts with Flashboot

Use Cases

  • Developing AI applications with popular frameworks like PyTorch and TensorFlow
  • Efficiently training and benchmarking AI models
  • Deploying production-ready models with serverless endpoints
  • Scalable inference and fine-tuning workloads with autoscaling
  • Cost-effective GPU rental for AI development

Suited For

  • Data scientists
  • Machine learning engineers
  • AI researchers
  • AI application developers


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