Side-by-Side Comparison · 2026

Amazon Bedrock vs Amazon SageMaker: Full Comparison (2026)

Amazon Bedrock is aws's managed service to build with frontier ai models from multiple providers. Amazon SageMaker is aws's fully managed platform to build, train, and deploy ml models at scale. Use the breakdown below to find the right fit for your needs.

Amazon Bedrock

Amazon Web Services

Paid
vs

Amazon SageMaker

Amazon Web Services

Paid
This page presents factual information sourced from publicly available vendor documentation and product pages. AIHub does not endorse either product. The right tool depends on your specific use case, team, and requirements — we recommend evaluating both tools directly before making a decision.

Side-by-Side Overview

Pricing Model
Amazon Bedrock: PaidAmazon SageMaker: Paid
API Access
Amazon Bedrock: AvailableAmazon SageMaker: Available
Platforms
Amazon Bedrock: AWS Console, API, AWS SDKs, Amazon SageMaker integrationAmazon SageMaker: AWS Console, SageMaker Studio, Python SDK
Integrations
Amazon Bedrock: 7 integrationsAmazon SageMaker: 8 integrations
Vendor
Amazon Bedrock: Amazon Web ServicesAmazon SageMaker: Amazon Web Services
Category
Amazon Bedrock: PlatformsAmazon SageMaker: Platforms
Launch
Amazon Bedrock: Apr 13, 2023 (preview); Sep 28, 2023 (GA)Amazon SageMaker: Nov 29, 2017
Models
Amazon Bedrock: Anthropic Claude 4, Meta Llama 4Amazon SageMaker: Any (bring your own or use JumpStart foundation models)

About Amazon Bedrock

Amazon Bedrock is a fully managed service from AWS that provides access to foundation models from Anthropic (Claude), Meta (Llama), Mistral, Cohere, Stability AI, Amazon Titan, and others via a single unified API. Enterprises use it to build and scale AI applications with AWS security, compliance, and cost management.

Designed For

  • Enterprise AI applications
  • RAG (knowledge bases)
  • Agents for task automation
  • Model evaluation
Full Amazon Bedrock details

About Amazon SageMaker

Amazon SageMaker is a fully managed machine learning service that covers the complete ML lifecycle: data labeling, feature engineering, model training, hyperparameter tuning, model evaluation, deployment, and monitoring. SageMaker JumpStart provides one-click access to hundreds of foundation models including Llama, Falcon, and Stable Diffusion.

Designed For

  • Enterprise ML model development
  • Foundation model fine-tuning
  • Batch ML inference
  • ML experiment management
Full Amazon SageMaker details

Strengths & Limitations

Amazon Bedrock

Strengths

  • Access to Claude, Llama, Mistral, Titan in one API
  • AWS security & compliance
  • Managed infrastructure
  • Bedrock Agents for agentic workflows
  • Fine-tuning support

Limitations

  • Complex pricing
  • AWS lock-in risk
  • Steeper learning curve
  • Cost at scale

Amazon SageMaker

Strengths

  • Deep AWS integration
  • Comprehensive end-to-end platform
  • SageMaker JumpStart (foundation models)
  • Auto-scaling
  • Managed notebooks

Limitations

  • Complex pricing
  • Steep learning curve
  • AWS vendor lock-in
  • Can be expensive

Frequently Asked Questions

What is the difference between Amazon Bedrock and Amazon SageMaker?

Amazon Bedrock is aws's managed service to build with frontier ai models from multiple providers, while Amazon SageMaker is aws's fully managed platform to build, train, and deploy ml models at scale. Amazon Bedrock is designed for Enterprise developers, AWS shops; Amazon SageMaker is designed for Enterprise ML teams, Data scientists at AWS-centric companies. The right fit depends on your specific requirements.

How do the pricing models compare?

Amazon Bedrock is available under a Paid model. Amazon SageMaker is available under a Paid model. Amazon Bedrock's entry tier starts at Per token (varies by model). Amazon SageMaker's entry tier starts at From $0.05/hr (t2.medium). Always verify pricing on each vendor's official website as it may change.

What integrations does each tool support?

Amazon Bedrock integrates with AWS Lambda, Amazon S3, Amazon OpenSearch, AWS Step Functions. Amazon SageMaker integrates with Amazon S3, Amazon EKS, Amazon Redshift, Apache Spark. Check each vendor's documentation for the full and current list.

How do I choose between Amazon Bedrock and Amazon SageMaker?

Consider your team's technical requirements, budget, existing tooling, and use case before deciding. We recommend signing up for free trials or demos of both tools where available, and consulting each vendor's documentation. AIHub provides this comparison for informational purposes only.