Compute Comparison

AWS vs RunPod: Pricing, Specs, Strengths & Weaknesses

Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for AWS and RunPod. Rates sourced from public APIs — verify current availability and billing terms before purchasing.

Overview

Attribute
Provider type
Hyperscaler
Specialist
Founded
2006
2022
Headquarters
Seattle, WA
San Francisco, CA
Billing model
On-demand, Reserved (1yr/3yr), Spot, Savings Plans
On-demand, Spot, Serverless (per-second)
Min commitment
None (on-demand)
None
Support tier
Basic → Enterprise
Community → Enterprise
Regions
5 regions
4 regions

Strengths & Best For

AWS

AWS EC2 P5 instances are powered by NVIDIA H100 Tensor Core GPUs (up to 8× H100, 640 GB HBM3, 3,200 Gbps EFA networking). P5e and P5en instances use NVIDIA H200 GPUs (up to 8× H200, 1,128 GB HBM3e). P5en adds Gen5 PCIe and third-generation EFA for 35% lower latency. All three families deploy in EC2 UltraClusters scaling to 20,000 GPUs with petabit-scale nonblocking networking delivering 20 exaflops aggregate. SageMaker HyperPod manages resilient training clusters at any scale. Amazon Bedrock provides serverless access to DeepSeek v3.2, MiniMax, Kimi 3, Z.AI GLM 5, and Writer Palmyra. 30+ global regions with enterprise SLAs.

Strengths
  • P5/P5e/P5en: H100 and H200 in UltraClusters up to 20,000 GPUs
  • 20 exaflops aggregate compute in EC2 UltraClusters
  • 3,200 Gbps EFA networking with GPUDirect RDMA
  • SageMaker HyperPod for resilient distributed training
  • Amazon Bedrock: serverless access to DeepSeek, MiniMax, Kimi, GLM, Palmyra
  • 30+ global regions with enterprise SLAs and compliance certifications
Weaknesses
  • Highest on-demand GPU rates among all providers
  • Complex pricing — on-demand vs reserved vs spot vs savings plans
  • GPU quota increases require support tickets and can take days
Best For
Hyperscale AI training requiring 1,000+ GPUsEnterprise workloads needing compliance (HIPAA, FedRAMP, SOC 2)Teams already invested in the AWS ecosystemProduction ML inference via SageMaker
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RunPod

RunPod is an AI developer cloud trusted by 1M+ developers, offering Pods (on-demand GPU instances), Serverless (autoscaling endpoints that scale to zero), and Clusters (multi-node distributed training) — all in one account. GPU catalog: B300, B200, H200, RTX PRO 6000, H100 NVL, H100 PCIe, H100 SXM, A100, L40S, RTX 4090, RTX 5090. Serverless and Clusters also available. Public Endpoints for instant model access. 31 global regions. SOC 2 Type II, HIPAA, GDPR compliant.

Strengths
  • B300, H200 — competitive Blackwell and Hopper pricing
  • RTX 5090 and RTX 4090 for budget inference
  • Serverless with sub-200ms cold starts (FlashBoot) and zero idle cost
  • Pods + Serverless + Clusters + Public Endpoints in one account
  • SOC 2 Type II, HIPAA, GDPR compliant
  • 31 global regions with per-second billing
Weaknesses
  • Community cloud tier hardware quality varies by host
  • Secure Cloud (network-isolated) costs more than community tier
  • Support response times slower on lower tiers
Best For
AI developers wanting one platform for all stagesServerless inference with zero idle costMulti-node distributed training via ClustersBudget-conscious teams needing RTX 4090/5090 inference
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Live GPU Pricing

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Region Coverage

AWS — 5 regions
us-east-1us-west-2eu-west-1ap-southeast-1ap-northeast-1

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Key differences

AWS

P5 (H100), P5e/P5en (H200), UltraClusters up to 20,000 GPUs — hyperscale AI infrastructure

RunPod

B300, H200, B200 — Pods, Serverless, and Clusters in one platform

AttributeAWSRunPod
Provider typehyperscalerspecialist
Billing modelOn-demand, Reserved (1yr/3yr), Spot, Savings PlansOn-demand, Spot, Serverless (per-second)
Min commitmentNone (on-demand)None
Regions5 (us-east-1, us-west-2, eu-west-1, +2)4 (US, EU, CA, +1)
Support tierBasic → EnterpriseCommunity → Enterprise
Best forHyperscale AI training requiring 1,000+ GPUs, Enterprise workloads needing compliance (HIPAA, FedRAMP, SOC 2)AI developers wanting one platform for all stages, Serverless inference with zero idle cost
Founded / HQ2006 · Seattle, WA2022 · San Francisco, CA