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AWS vs RunPod

Compare AWS vs RunPod across 5 shared on-demand GPU rows. RunPod is cheaper on 5 shared on-demand GPUs, while AWS is cheaper on 0.

View AWS View RunPod
AWS wins
0
cheaper shared GPUs
RunPod wins
5
cheaper shared GPUs
Shared GPUs
5
19 rows with either provider
Average savings
60%
RunPod leads overall
Search guide

AWS vs RunPod: how to read the comparison

Provider comparison pages are most useful when they separate shared GPU economics from catalog breadth. Start with the shared on-demand rows, then open provider detail pages for spot, community, and workload-specific slices.

A provider can win the cheapest shared row while still being a worse fit for your workload if it lacks the GPU family, pricing mode, or operational model you need.

Cheapest provider right now

Current shared-row winner

RunPod is cheaper on 5 shared on-demand GPUs, while AWS is cheaper on 0.

Methodology and freshness

How provider wins are computed

We compare the latest on-demand median price for each GPU that appears on either provider, count wins only when both providers have a row, and keep missing rows visible as coverage gaps.

FAQ

AWS vs RunPod FAQ

Which is cheaper, AWS or RunPod?

RunPod is cheaper on 5 shared on-demand GPUs, while AWS is cheaper on 0.

How many GPUs can I compare between AWS and RunPod?

The current comparison has 5 shared on-demand GPU rows and 19 total rows where at least one provider has pricing.

Why does this comparison focus on on-demand pricing?

On-demand is the most consistent baseline across hyperscalers and specialist GPU clouds. Spot and community rows can be cheaper, but they are less uniformly available across provider pairs.

How fresh is the AWS vs RunPod comparison?

This page recalculates from the latest stored provider snapshots. The freshest row in this comparison set is from Jul 31, 2026.

Popular follow-up searches

Related provider comparisons

Use these pages to compare adjacent provider choices without returning to the homepage.

AWS GPU prices Open the full provider page and workload slices. RunPod GPU prices Open the full provider page and workload slices. AWS vs Lambda Compare another provider pair. AWS vs Vast.ai Compare another provider pair. RunPod vs Lambda Compare another provider pair. RunPod vs Vast.ai Compare another provider pair.

On-demand pricing by GPU

GPU VRAM
AWS
RunPod
Cheaper Savings
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More provider comparisons

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Agent-assisted setup

Hand this runbook to Claude Code or Codex

Open a terminal in the repository where you want the deployment files, start claude or codex, then paste this prompt. It asks the agent to verify sources and stop before it creates billable infrastructure.

Claude Code quickstart ↗ Codex docs ↗
Deployment prompt 
Use the infrastructure or model context on this page to create a reproducible open-model deployment. Use this guide as the starting context: https://www.getflops.ai/aws-vs-runpod. Read the linked model card and provider documentation before choosing hardware or runtime settings. Open every linked primary source and flag any mismatch instead of guessing. Create a deployment folder containing README.md, .env.example with no secrets, a pinned start script or infrastructure manifest, and smoke-test.sh. Make the endpoint OpenAI-compatible where the runtime supports it. Run local/static validation, estimate the billable resources, and stop before provisioning paid infrastructure until I approve.
Guardrails included No secrets in files · verify primary docs · approval before spend