# Runpod

> Cloud GPUs and serverless infrastructure for AI workloads

Runpod is a cloud computing platform for building, training, and serving AI models without buying GPU hardware. Developers can launch a Pod from a ready-made template or their own Docker image, then work through SSH, JupyterLab, or a local editor. Persistent network volumes keep datasets and model weights separate from the life of a compute instance. For production applications, Serverless turns containerized workloads into API endpoints with automatic worker scaling and optional scale-to-zero behavior. GPU clusters support larger distributed training and inference jobs. A team can use the same platform to experiment with a model, fine-tune it on its own data, and deploy it behind an endpoint, choosing hardware and capacity to suit each stage.

## Listing details

- Canonical BetaNeon page: https://betaneon.com/products/runpod
- Official website: https://www.runpod.io/
- Category: Developer tools / Cloud hosting & deployment
- Status: Launched
- Topics: Cloud computing, GPU, Inference, Machine learning, Serverless
- Listing updated: 2026-10-30T16:53:22.470Z
- Information source: https://www.runpod.io/

This is a product introduction, not an endorsement. Confirm current availability, features, and prices on the official website. Community upvotes on BetaNeon are not star ratings.