Amazon SageMaker
Amazon Web Services
PaidGoogle Vertex AI
Google Cloud
PaidAmazon SageMaker vs Google Vertex AI: Full Comparison (2026)
Amazon SageMaker is aws's fully managed platform to build, train, and deploy ml models at scale. Google Vertex AI is google cloud's unified ml platform for enterprise ai at scale. Use the breakdown below to find the right fit for your needs.
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 SageMaker
PaidGoogle Vertex AI
PaidAPI Access
Amazon SageMaker
AvailableGoogle Vertex AI
AvailablePlatforms
Amazon SageMaker
AWS Console, SageMaker Studio, Python SDKGoogle Vertex AI
Google Cloud Console, Python SDK, REST API, gcloud CLIIntegrations
Amazon SageMaker
8 integrationsGoogle Vertex AI
7 integrationsVendor
Amazon SageMaker
Amazon Web ServicesGoogle Vertex AI
Google CloudCategory
Amazon SageMaker
PlatformsGoogle Vertex AI
PlatformsLaunch
Amazon SageMaker
Nov 29, 2017Google Vertex AI
May 18, 2021 (Vertex AI launch)Models
Amazon SageMaker
Any (bring your own or use JumpStart foundation models)Google Vertex AI
Gemini 2.5 Pro/Flash, Gemini 3.5 Flash| Feature | Amazon SageMaker | Google Vertex AI |
|---|---|---|
| Pricing Model | Paid | Paid |
| API Access | Available | Available |
| Platforms | AWS Console, SageMaker Studio, Python SDK | Google Cloud Console, Python SDK, REST API, gcloud CLI |
| Integrations | 8 integrations | 7 integrations |
| Vendor | Amazon Web Services | Google Cloud |
| Category | Platforms | Platforms |
| Launch | Nov 29, 2017 | May 18, 2021 (Vertex AI launch) |
| Models | Any (bring your own or use JumpStart foundation models) | Gemini 2.5 Pro/Flash, Gemini 3.5 Flash |
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
About Google Vertex AI
Google Vertex AI is Google Cloud's end-to-end machine learning platform that unifies access to Gemini models, third-party models, AutoML, custom model training, MLOps, and AI infrastructure. It offers Vertex AI Agent Builder, Grounding with Google Search, model evaluation, and Vector Search for enterprise RAG applications.
Designed For
- Enterprise AI pipelines
- Custom model training
- RAG applications
- MLOps
Strengths & Limitations
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
Google Vertex AI
Strengths
- Access to all Gemini models
- Grounding with Google Search
- AutoML capabilities
- Enterprise-grade security
- Model Garden (150+ models)
Limitations
- Google Cloud dependency
- Complex pricing
- Learning curve
- Slower iteration vs OpenAI
Frequently Asked Questions
What is the difference between Amazon SageMaker and Google Vertex AI?
Amazon SageMaker is aws's fully managed platform to build, train, and deploy ml models at scale, while Google Vertex AI is google cloud's unified ml platform for enterprise ai at scale. Amazon SageMaker is designed for Enterprise ML teams, Data scientists at AWS-centric companies; Google Vertex AI is designed for Google Cloud enterprises, Data science teams. The right fit depends on your specific requirements.
How do the pricing models compare?
Amazon SageMaker is available under a Paid model. Google Vertex AI is available under a Paid model. Amazon SageMaker's entry tier starts at From $0.05/hr (t2.medium). Google Vertex AI's entry tier starts at Per token/compute hour. Always verify pricing on each vendor's official website as it may change.
What integrations does each tool support?
Amazon SageMaker integrates with Amazon S3, Amazon EKS, Amazon Redshift, Apache Spark. Google Vertex AI integrates with BigQuery, Cloud Storage, Kubernetes (GKE), Looker. Check each vendor's documentation for the full and current list.
How do I choose between Amazon SageMaker and Google Vertex AI?
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.
Feature Snapshot
Explore Further
Amazon SageMaker full detailsGoogle Vertex AI full detailsAmazon SageMaker official siteGoogle Vertex AI official siteRelated Comparisons
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Data sourced from public vendor documentation. Pricing, features, and availability may change. Always verify on official vendor websites before making purchasing decisions. AIHub is not affiliated with any of the listed vendors.