RunPod

What is RunPod?

RunPod is a cloud platform providing on-demand GPU infrastructure for AI development, training, and inference. It offers persistent pods, autoscaling serverless endpoints, and multi-node clusters across 31 global regions, accessible through a single account without contracts or minimum commitments.

What are the features of RunPod?

• On-demand GPU instances (Pods)

  Deploy persistent GPU environments in under a minute, available as reserved or interruptible spot instances from over 30 GPU SKUs including B200s and RTX 4090s.
• Autoscaling serverless endpoints

  Run API-based workloads that scale from zero to thousands of workers with sub-200ms cold starts using FlashBoot, incurring no cost when idle.
• Multi-node GPU clusters

  Execute distributed training and large-batch inference across 200+ simultaneous GPUs connected via InfiniBand.
• Persistent network storage

  Attach network volumes to share memory and model weights across workers without egress fees.
• Managed task orchestration

  Built-in job queues distribute tasks automatically, removing the need for custom orchestration systems.
• Agent deployment support

  The Runpod skills package enables coding agents like Claude Code and Cursor to deploy and manage resources directly.

What are the use cases of RunPod?

• Production inference serving

  Handle live application traffic scaling from zero to over 1,000 requests per second on serverless endpoints without paying for idle capacity.
• Browser-based AI game hosting

  Run interactive applications like a murder mystery game by deploying open-source models such as Qwen3 32B and FLUX.1 Schnell on public endpoints.
• Distributed model training

  Fine-tune AI models faster by provisioning multi-node clusters with dedicated high-bandwidth networking.

How to use RunPod?

1. Launch environment

   Spin up a GPU pod or configure a serverless endpoint within a single account.
2. Build workload

   Run your own containers, frameworks, and code to train models, fine-tune, or process data.
3. Deploy handler

   Write and push your inference handler to Serverless to create a live endpoint with automatic scaling.

RunPod Pricing Information:

• Free access

  Getting started is free; specific compute quotas or credit amounts are not stated.
• On-demand compute

  GPU capacity is rented by the hour or second with no contracts or minimum commitments. Spot instances are available at a lower price than reserved instances.
• Serverless

  Costs apply only while the endpoint processes requests, with zero cost during idle periods.
• Enterprise

  Adds a 99.99% uptime SLA, dedicated capacity, and tailored terms; requires contacting sales.