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What's the Difference Between AWS Deep Learning AMIs and AWS DL Containers?

Compare AWS Deep Learning AMIs and AWS DL Containers side by side — features, pricing, and ideal use cases to help you choose the right product.

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Comparisons
AWS Deep Learning AMIs
AWS DL Containers
Category

Machine Learning, Development Environment

Machine Learning, Container Images
Description

Pre-configured Amazon Machine Images with popular deep learning frameworks for EC2.

Docker images pre-installed with deep learning frameworks for training and inference.
Best for
  • Deep learning development
  • Model training
  • Research
  • Prototyping
  • Containerized ML training
  • ML inference
  • Distributed training
  • CI/CD for ML
Key features
  • Pre-installed frameworks
  • GPU optimized
  • Conda environments
  • CUDA/cuDNN
  • Multiple OS support
  • Pre-built images
  • ECS/EKS/SageMaker support
  • Multi-framework
  • GPU optimized
  • ECR hosted
Pricing model

No additional charge; pay for EC2 instances

No additional charge; pay for underlying compute
Free tier

Yes

Yes
Expert take

“Deep Learning AMIs come pre-installed with PyTorch, TensorFlow, and MXNet on optimized NVIDIA drivers. They eliminate framework installation and driver compatibility issues.”
— Didier Durand, re:Post Top Contributor [profile]

“Deep Learning Containers are Docker images pre-built with ML frameworks for ECS, EKS, and SageMaker. They include optimizations for AWS hardware like Inferentia and Trainium.”
— Gary McLean, re:Post Top Contributor [profile]
Product page

Learn more about AWS Deep Learning AMIs »

Learn more about AWS DL Containers »

When to use AWS Deep Learning AMIs or AWS DL Containers

Use AWS Deep Learning AMIs when:

  • Deep learning development
  • Model training
  • Research
  • Prototyping

Learn more about AWS Deep Learning AMIs »

Use AWS DL Containers when:

  • Containerized ML training
  • ML inference
  • Distributed training
  • CI/CD for ML

Learn more about AWS DL Containers »

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