RunPod
Community and secure GPU cloud for AI inference and training.
Description
RunPod is a GPU cloud platform founded in 2022 by Zhen Lu and Pardeep Singh, built from a Go-based MVP the two co-founders developed over three months after Singh convinced Lu to start the company. Headquartered originally in Mount Laurel, New Jersey and backed by a $20M seed round led by Intel Capital, the platform runs on two tiers: Community Cloud, where individual GPU owners contribute hardware to a shared pool, and Secure Cloud, which uses data-center-hosted nodes with guaranteed availability. Over 750,000 developers use the platform across AI inference, training, fine-tuning, and workloads that range from ML research to HealthTech and FinTech.
Key Capabilities:
On-demand GPU Pods with full Docker environment control and SSH access
Community Cloud tier for lowest-cost spot-like GPU access
Secure Cloud tier for guaranteed data-center-hosted GPU availability
Serverless GPU autoscaling endpoints for production inference
Flash Python SDK for deploying any function as a GPU-backed endpoint
Multi-node GPU clusters deployable in under ten minutes
Per-second billing with no long-term commitments or contracts
Wide GPU selection including RTX 4090, A100, and H100
Persistent network storage across pod restarts
AI agent deployment and model fine-tuning support
Global networking across 30+ regions
SOC 2 Type II compliance for data protection
REST API and CLI for programmatic workload management
Alternative tools
- Hugging Face Inference
Serverless and dedicated inference across 500,000+ Hub models.
- Beam Cloud
Open-source serverless GPU platform for inference, sandboxes, and agents.
- Lambda Labs
GPU cloud and on-premise AI infrastructure for ML teams.
- Koyeb
Serverless platform for apps, inference, and AI agent deployment.
- Northflank
Deploy and scale workloads on your own cloud infrastructure.
- Modal
Serverless GPU platform for AI inference, training, and batch jobs.