Amazon SageMaker Autopilot
Plans
| Plan | Billed and limits | Price |
|---|---|---|
| On-demand | Pay only for resources used · No minimum fees · No upfront commitments | On request |
| Savings Plans | Flexible usage-based pricing · Requires a commitment to consistent usage | On request |
| Amazon SageMaker AI pay-as-you-go | Pay only for what you use; on-demand pricing has no minimum fees or upfront commitments. · Autopilot-specific rate not stated · SageMaker AI Free Tier includes 160 hours/month of Canvas session time for the first 2 months | Free |
| SageMaker AI Free Tier | First 2 months after creating the first SageMaker AI resource · 250 hours ml.t3.medium notebooks · 50 training hours · 125 real-time inference hours · 160 Canvas hours/month · 150,000 serverless-inference seconds | Free |
| On-demand SageMaker AI | Usage-based; no minimum fees or upfront commitments · Underlying compute, storage, processing and feature usage billed separately | On request |
As aws.amazon.com lists them, read 21 Sept 2026. The maker's own page has the final word.
Facts from Amazon SageMaker Autopilot's own pages
- API
- The public Autopilot REST API includes CreateAutoMLJob, CreateAutoMLJobV2, DescribeAutoMLJob, DescribeAutoMLJobV2 and ListAutoMLJobs operations. · docs.aws.amazon.com, 19 Oct 2026
- Automatic model selection
- Autopilot infers problem types such as binary classification, multiclass classification, regression and time-series forecasting, then evaluates many candidate algorithms. · aws.amazon.com, 19 Oct 2026
- Canvas migration
- Since November 30, 2023, the Autopilot user interface has been migrating into SageMaker Canvas, while Studio Classic users can continue using the older interface. · docs.aws.amazon.com, 19 Oct 2026
- Compliance
- AWS provides compliance information and resources for customers to understand AWS services’ compliance status. · aws.amazon.com, 30 Sept 2026
- Customization
- Users can apply their own transformations alongside more than 300 preconfigured data transformations and customize data splits and training options. · aws.amazon.com, 30 Sept 2026
- Data preparation
- It can fill missing data, provide statistical insights about dataset columns, and extract information from non-numeric columns. · aws.amazon.com, 30 Sept 2026
- Data preprocessing
- Autopilot handles missing values, normalizes data, selects features and prepares training data automatically. · docs.aws.amazon.com, 19 Oct 2026
- Deployment
- After training, users can deploy Autopilot models to real-time endpoints or run batch inference jobs. · docs.aws.amazon.com, 19 Oct 2026
- Documentation depth
- AWS publishes separate user guides, API references, deployment instructions, algorithm-support pages and quota documentation for Autopilot. · docs.aws.amazon.com, 19 Oct 2026
- Explainability
- Autopilot generates feature-importance and model-performance reports, including confusion matrices and ROC or precision-recall visualizations where supported. · docs.aws.amazon.com, 19 Oct 2026
- Feature engineering
- The product offers more than 300 preconfigured data transformations and allows custom preprocessing and feature-engineering steps. · aws.amazon.com, 19 Oct 2026
- Founded
- 2006 · aws.amazon.com, 28 Sept 2026
- Free tier
- SageMaker AI’s Free Tier runs for the first two months from the first month a customer creates a SageMaker AI resource and includes 160 hours/month of Canvas session time. · aws.amazon.com, 30 Sept 2026
- Generated notebooks
- Autopilot can generate a SageMaker Studio Notebook for a created model so users can inspect, refine, and recreate it. · aws.amazon.com, 30 Sept 2026
- Headquarters
- Seattle, Washington, United States · aws.amazon.com, 28 Sept 2026
- Input quota
- The default input-dataset quota is 100 GB and can be increased to hundreds of gigabytes; a single Parquet file is limited to 2 GB. · docs.aws.amazon.com, 19 Oct 2026
- Integrations
- Reviewer evidence describes integrations with Amazon S3, IAM, CloudWatch and ECR, while AWS documents Studio and Canvas integration. · gartner.com, 19 Oct 2026
- Kubeflow integration
- AWS provides open-source SageMaker components for Kubeflow Pipelines to use SageMaker for labeling, training and inference steps. · aws.amazon.com, 19 Oct 2026
- Leaderboard
- Experiments produce a ranked model leaderboard with metrics such as accuracy and precision for choosing a deployment candidate. · aws.amazon.com, 19 Oct 2026
- Limit: complexity and interface
- G2 reviewers report that SageMaker can feel overcomplicated, with a cluttered interface and pipeline tooling that is less friendly than alternatives. · g2.com, 19 Oct 2026
- Limit: cost
- Gartner reviewer feedback repeatedly identifies SageMaker's price points and expense as a drawback. · gartner.com, 19 Oct 2026
- Limit: image handling
- G2 reviewers describe difficulties passing image data to some models and note that image-focused data support can be limited. · g2.com, 19 Oct 2026
- Limit: runaway costs
- A Capterra reviewer warns that leaving domains or resources active can incur charges quickly. · capterra.com, 19 Oct 2026
- Limit: scheduling and metrics
- A TrustRadius reviewer reports that SageMaker lacks easy scheduling for training jobs and straightforward tracking of metrics logged during training. · trustradius.com, 19 Oct 2026
Where Amazon SageMaker Autopilot stands on Freedom251
- AutoML Software#7 of 30
- Model registries#13 of 38