R

Pods

Infrastructure service

by RunPod

Per-hour GPU pods and per-hour serverless endpoints across both datacentre accelerators and consumer cards, sold on price — the company's own claim is compute up to 90% below traditional cloud providers.

Find alternatives to Pods

Secure Cloud pods per GPU-hour: B300 $7.89, B200 $6.79, H200 $4.59, H100 SXM $3.29, H100 NVL $3.19, H100 PCIe $2.89, RTX Pro 6000 $2.09, A100 SXM $1.59, A100 PCIe $1.39, L40S $0.99, RTX 5090 $0.99, RTX 6000 Ada $0.84, L40 $0.82, RTX 4090 $0.74, RTX A6000 $0.53, RTX 3090 $0.50, L4 $0.49, A40 $0.44, RTX A5000 $0.27. Serverless is dearer per hour: B300 $9.98, H200 $5.93, H100 $4.79, L40/L40S $1.75, RTX 4090 $1.10. Storage: network $0.07/GB/month under 1TB and $0.05 above, container disk $0.10/GB/month.

What it does

• GPU cloud
• Model inference
• Model training

How it compares

• Lambda On-Demand Instances

  Runpod and Lambda.ai (Lambda Labs) compete for the same buyer: an AI team that wants GPU capacity without signing a hyperscaler contract.

  Official documentation · 19 Sep 2026
• Together GPU Clusters

  RunPod, founded in 2022, is a cloud-based infrastructure service that provides cost-effective and scalable GPU resources.

  Research report · 19 Sep 2026
• CoreWeave AI Cloud

  Both Runpod and CoreWeave offer on-demand access to high-performance GPUs for AI workloads. This comparison covers how each handles AI image generation, across GPU selection, cost, containerization, customizability, ease of deployment, community support, integrations, and APIs.

  Official documentation · 19 Sep 2026

Sources

Pricing

Pricing page · 4 Sep 2026

Every per-hour rate, the serverless tier and both storage rates read from the page 2026-09-04.

Description

Official documentation · 4 Sep 2026

Its own claim on that page: "GPU cloud computing with compute costs up to 90% lower than traditional cloud providers."

Sold within

Pricing page · 30 Sep 2026

The pricing page says "Runpod pricing depends on the GPU workload you run: Pods for dedicated GPU instances, Serverless for API inference, and Clusters for multi-node jobs." and lists per-hour Pod rates per GPU with a "Deploy" button on each.

Also from RunPod

• Serverless Infrastructure service

  Autoscaling GPU API endpoints for AI inference, billed per second with scale-to-zero and sub-200ms cold starts.

• Runpod Clusters Infrastructure service

  Multi-node GPU environments with high-speed InfiniBand interconnect for distributed training and large batch workloads.

• Runpod Hub Developer tool

  A catalog of templates, models and open-source AI apps that can be forked and deployed onto Runpod Serverless in one click.

• Public Endpoints Model API

  Instant API access to pre-deployed third-party AI models for image, video, audio and text generation, billed per request or per token with no infrastructure setup.

• Runpod Hybrid Cloud Platform

  Brings customer-owned or rented GPU hardware under Runpod's console, CLI and APIs as a single control plane, with Runpod cloud used for overflow capacity.

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