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Rent cloud GPUs for AI training, inference, and compute workloads
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.
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