Amazon AWS vs RunPod

Compare GPU pricing, features, and specifications between Amazon AWS and RunPod cloud providers. Find the best deals for AI training, inference, and ML workloads.

Amazon AWS logo

Amazon AWS

Provider 1

6
GPUs Available
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RunPod logo

RunPod

Provider 2

15
GPUs Available
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Comparison Overview

16
Total GPU Models
Amazon AWS logo
6
Amazon AWS GPUs
RunPod logo
15
RunPod GPUs
5
Direct Comparisons

Average Price Difference: $1.80/hour between comparable GPUs

View:
Amazon AWS
RunPod

GPU Pricing Comparison

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Features Comparison

Amazon AWS

  • Global Infrastructure

    Extensive network of data centers across multiple regions worldwide

  • Pay-as-you-go Pricing

    Flexible pricing model with no upfront commitments required

  • Advanced Security

    Comprehensive security tools and compliance certifications

  • Auto Scaling

    Automatically adjust resources based on demand

  • Integrated Services

    Extensive ecosystem of services that work seamlessly together

  • Developer Tools

    Comprehensive suite of tools for development, deployment, and management

RunPod

  • Secure Cloud GPUs

    Access to a wide range of GPU types with enterprise-grade security

  • Pay-as-you-go

    Only pay for the compute time you actually use

  • API Access

    Programmatically manage your GPU instances via REST API

  • Fast cold-starts

    Pods typically ready in 20-30 s

  • Hot-reload dev loop

    SSH & VS Code tunnels built-in

  • Spot-to-on-demand fallback

    Automatic migration on pre-empt

Pros & Cons

Amazon AWS

Advantages
  • Broad range of compute options including GPUs
  • Highly scalable and reliable infrastructure
  • Pay-as-you-go pricing with cost optimization tools
  • Extensive global network of data centers
Considerations
  • Complex pricing structure
  • Steep learning curve for new users
  • Potential for unexpected costs without proper management

RunPod

Advantages
  • Competitive pricing with pay-per-second billing
  • Wide variety of GPU options
  • Simple and intuitive interface
Considerations
  • GPU availability can vary by region
  • Some features require technical knowledge

Compute Services

Amazon AWS

Amazon EC2

Virtual servers in the cloud with a wide range of instance types.

Amazon ECS

Fully managed container orchestration service.

  • Support for Docker containers
  • Integration with other AWS services
Amazon EKS

Managed Kubernetes service for container orchestration.

  • Certified Kubernetes conformant
  • Integrates with AWS networking and security services

RunPod

Pricing Options

Amazon AWS

On-Demand Instances

Pay for compute capacity by the second with no long-term commitments.

Spot Instances

Use spare EC2 capacity at up to 90% off the On-Demand price.

Reserved Instances

Save up to 72% compared to On-Demand pricing with a 1 or 3-year commitment.

Savings Plans

Save up to 72% on compute usage with a 1 or 3-year commitment to a consistent amount of usage.

RunPod

Getting Started

Amazon AWS

Get Started
  1. 1
    Sign up for AWS

    Create an AWS account to access the cloud platform.

  2. 2
    Choose a compute service

    Select from EC2, Lambda, or container services based on your workload needs.

  3. 3
    Launch an instance

    Configure and launch your first compute instance or container.

  4. 4
    Set up security

    Configure security groups and access controls for your resources.

  5. 5
    Monitor and optimize

    Use AWS CloudWatch and Compute Optimizer to monitor performance and reduce costs.

  1. 1
    Create an account

    Sign up for RunPod using your email or GitHub account

  2. 2
    Add payment method

    Add a credit card or cryptocurrency payment method

  3. 3
    Launch your first pod

    Select a template and GPU type to launch your first instance

Support & Global Availability

Amazon AWS

Global Regions

25+ regions and 80+ availability zones worldwide.

Support

Basic (free), Developer, Business, Enterprise support plans with varying response times and features. Extensive documentation, forums, and training resources.

RunPod