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AWS vs Packet AI: GPU Compute Price Comparison

Side-by-side comparison of GPU compute pricing, regions, billing models, and strengths for AWS and Packet AI. Updated July 2026.

Provider Overview

Attribute
Provider type
Hyperscaler
Bare-metal
Founded
2006
2023
Headquarters
Seattle, WA
United States
Billing model
On-demand, Reserved (1yr/3yr), Spot
On-demand
Min commitment
None (on-demand)
None
Support tier
Basic → Enterprise
Standard
Regions
5 regions
1 regions

Strengths & Best For

AWS

AWS offers on-demand, reserved, and spot GPU instances across EC2 P4d (A100), P5 (H100), and G6 (L40S) families, spanning 30+ global regions with enterprise SLAs and deep ML tooling via SageMaker. H100 and A100 clusters are available with InfiniBand networking for distributed LLM training and large-scale AI inference. The broadest ecosystem of any GPU cloud provider, making it the default choice for enterprises already invested in the AWS stack.

Strengths
  • Widest global region coverage
  • Deep ecosystem integrations
  • Enterprise SLAs
  • Reserved instance discounts
Best For
Enterprise workloadsProduction ML inferenceTeams already on AWS
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Packet AI

Packet AI provides bare-metal L40S and H100 GPU servers with no virtualization overhead and straightforward on-demand billing, making it a cost-effective option for AI inference and training workloads that need dedicated hardware performance. Bare-metal configurations eliminate the latency and overhead of hypervisor layers, delivering consistent GPU throughput for production LLM inference and model deployment. A practical choice for teams that need dedicated GPU hardware without the complexity of managed cloud services.

Strengths
  • Competitive L40S pricing
  • Bare metal performance
  • No virtualisation overhead
  • Simple billing
Best For
Inference workloadsCost-sensitive L40S usersBare metal performance
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Live GPU Pricing

No live pricing data available for these providers right now. View all live GPU prices →

Region Coverage

AWS5 regions
us-east-1us-west-2eu-west-1ap-southeast-1ap-northeast-1

Popular Comparisons

AWShyperscaler provider

AWS offers on-demand, reserved, and spot GPU instances across EC2 P4d (A100), P5 (H100), and G6 (L40S) families, spanning 30+ global regions with enterprise SLAs and deep ML tooling via SageMaker. H100 and A100 clusters are available with InfiniBand networking for distributed LLM training and large-scale AI inference. The broadest ecosystem of any GPU cloud provider, making it the default choice for enterprises already invested in the AWS stack.

Packet AIbare-metal provider

Packet AI provides bare-metal L40S and H100 GPU servers with no virtualization overhead and straightforward on-demand billing, making it a cost-effective option for AI inference and training workloads that need dedicated hardware performance. Bare-metal configurations eliminate the latency and overhead of hypervisor layers, delivering consistent GPU throughput for production LLM inference and model deployment. A practical choice for teams that need dedicated GPU hardware without the complexity of managed cloud services.

Billing model comparison

AWS uses a On-demand, Reserved (1yr/3yr), Spot billing model with a minimum commitment of None (on-demand). Packet AI uses On-demand billing with a None minimum. AWS's no-commitment on-demand model is more flexible for short-term or experimental workloads, while Packet AI's commitment requirement suits teams with predictable long-running jobs.

Which workloads each provider suits best

AWS is best suited for: Enterprise workloads, Production ML inference, Teams already on AWS. Its key strengths are widest global region coverage, deep ecosystem integrations, enterprise slas. Packet AI is best suited for: Inference workloads, Cost-sensitive L40S users, Bare metal performance. Its key strengths are competitive l40s pricing, bare metal performance, no virtualisation overhead. Both providers target similar workload profiles — the live pricing table above is the most reliable way to determine which offers better value for your specific GPU model and region requirements.

Support tiers and region coverage

AWS offers Basic → Enterprise support across 5 regions (us-east-1, us-west-2, eu-west-1 and 2 more). Packet AI offers Standard support across 1 region (US). AWS's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.

Provider background: AWS vs Packet AI

AWS was founded in 2006 and is headquartered in Seattle, WA. Packet AI was founded in 2023 and is headquartered in United States. AWS has 17 years more operational history than Packet AI, which may matter for teams evaluating provider stability and long-term contract risk. Use the live pricing table above to compare current on-demand and spot rates for specific GPU models, and the region map to verify coverage in your target geography.