Machine Learning · head to head
AWS SageMaker vs Windsurf
AWS SageMaker
Machine Learning
Build, train, and deploy machine learning models at scale
- From
- Free
- Rated
- -
The short version
- Each has a real cost: AWS SageMaker vendor lock-in to AWS ecosystem makes migration to other platforms difficult; Windsurf recently rebranded to Devin Desktop, creating product identity confusion
- They diverge on capability: AWS SageMaker covers Jupyter notebooks, Windsurf covers Cascade AI agent.
Where they differ
Only the attributes on which AWS SageMaker and Windsurf actually diverge.
| Attribute | AWS SageMaker | Windsurf |
|---|---|---|
| Platforms | Web | macOS, Linux, Windows |
| Category | Machine Learning | Software Development |
| Founded | 2006 | 2021 |
Identical on both: starting price (Free), pricing model (Unknown), free tier (Yes), user rating (Not yet rated).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in AWS SageMaker
- Jupyter notebooks
- Built-in algorithms
- Automatic model tuning
- One-click deployment
- Model monitoring
- S3
- Lambda
- Step Functions
Only in Windsurf
- Cascade AI agent
- Agentic programming
- Context-aware assistance
- Automated command execution
- Multi-file understanding
- Intelligent code generation
- Real-time debugging
- Integrated terminal
What people use each for
The jobs each tool is most often brought in to do.
AWS SageMaker
- Machine learningnot Windsurf
- Data analysisnot Windsurf
- Model trainingnot Windsurf
- Predictive analyticsnot Windsurf
Windsurf
- Agentic developmentnot AWS SageMaker
- AI-assisted codingnot AWS SageMaker
- Complex project managementnot AWS SageMaker
- Automated coding tasksnot AWS SageMaker
- Learning new codebasesnot AWS SageMaker
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
AWS SageMaker
- Vendor lock-in to AWS ecosystem makes migration to other platforms difficult
- Opaque pricing can lead to unexpected expenses like forgotten EBS volume charges
- Does not include native job scheduling, requiring Lambda or EventBridge integration
Windsurf
- Recently rebranded to Devin Desktop, creating product identity confusion
- Cascade agent reached end-of-life on July 1, 2026, requiring migration to Devin Local
- Free tier quota runs out quickly for active developers, within a couple days of coding
- Pricing increased significantly in March 2026 overhaul, moving from credit-based to daily/weekly quotas
- OpenAI acquisition raises concerns about long-term product direction diverging from Codeium's vision
Pricing, plan by plan
AWS SageMaker
FreeNo published plan breakdown. See the AWS SageMaker review.
Windsurf
Free- FreeFree
- Light daily and weekly quotas
- Unlimited tab autocomplete
- Access to Cascade AI agent
- Pro$20/month
- Standard quotas
- Windsurf proprietary SWE model
- Cloud sessions for background work
- Max$200/month
- Heavy daily quotas
- Long agent sessions
- Frontier third-party models
- Teams$40/month-per-user
- All Pro features
- Centralized billing
- Usage analytics
Which should you pick?
Choose AWS SageMaker if
- You need jupyter notebooks.
- You want to start without paying.
- You also want built-in algorithms.
Choose Windsurf if
- You need cascade ai agent.
- You want to start without paying.
- You work on macOS, Linux, Windows.
- You also want agentic programming.
Questions people ask
- Is AWS SageMaker or Windsurf better?
- Neither clearly leads. AWS SageMaker starts at Free and Windsurf at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, AWS SageMaker or Windsurf?
- AWS SageMaker starts at Free and Windsurf at Free.
- Does AWS SageMaker or Windsurf run on more platforms?
- AWS SageMaker runs on Web. Windsurf runs on macOS, Linux, Windows.
- Can I use AWS SageMaker for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is AWS SageMaker best used for?
- AWS SageMaker is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Windsurf is typically brought in for.
- What can AWS SageMaker do that Windsurf cannot?
- AWS SageMaker covers Jupyter notebooks, Built-in algorithms, Automatic model tuning, One-click deployment. Windsurf covers Cascade AI agent, Agentic programming, Context-aware assistance, Automated command execution.
Answered from the vendors’ own pages
AWS SageMaker: What is AWS SageMaker used for?
AWS SageMaker is a machine learning service for building, training, and deploying ML models at scale. It provides tools for data preparation, model training, inference endpoints, and performance optimization.
SourceWindsurf: Does Windsurf support MCP (Model Context Protocol) integrations?
Yes. Windsurf supports MCP with integrations for 21 third-party tools for extending functionality and connecting to external systems.
SourceAWS SageMaker: How is AWS SageMaker priced?
SageMaker uses pay-as-you-go pricing with no upfront costs or long-term commitments. Pricing starts at $0.04 per hour for basic notebook instances and scales based on instance type. ML Savings Plans offer up to 64% off with hourly spend commitments.
SourceWindsurf: What is Windsurf's current status as of 2026?
Windsurf rebranded to Devin Desktop in June 2026 and is backed by OpenAI after its 2025 acquisition. Cascade reached end-of-life on July 1, 2026, with Devin Local as the Rust-rewritten successor.
SourceAWS SageMaker: Does AWS SageMaker have a free tier?
Yes, the free tier includes 250 hours of notebook usage, 50 hours of training, and 125 hours of hosting on ml.t3.medium instances during the first two months.
SourceRelated pages
More on AWS SageMaker
Other head to heads
- AWS SageMaker vs Google Vertex AI
- AWS SageMaker vs Azure Machine Learning
- AWS SageMaker vs DataRobot
- AWS SageMaker vs MLflow
- AWS SageMaker vs Snowflake
- AWS SageMaker vs TensorFlow
- AWS SageMaker vs Comet ML
- AWS SageMaker vs Jupyter
- AWS SageMaker vs LangChain
- AWS SageMaker vs Pinecone
- AWS SageMaker vs Python
- AWS SageMaker vs PyTorch
- AWS SageMaker vs scikit-learn
- AWS SageMaker vs Apache Spark MLlib
- AWS SageMaker vs Weaviate
- AWS SageMaker vs Weights & Biases
- AWS SageMaker vs Alteryx
- AWS SageMaker vs Anaconda
- AWS SageMaker vs Cursor
- AWS SageMaker vs Zed
- AWS SageMaker vs Amp
- AWS SageMaker vs Braintrust
- AWS SageMaker vs Codacy
- AWS SageMaker vs DeepSource
- AWS SageMaker vs Devin
- AWS SageMaker vs SonarQube Cloud
- AWS SageMaker vs Augment Code
- AWS SageMaker vs Baseten
- AWS SageMaker vs Drizzle ORM
- AWS SageMaker vs Flagsmith
- AWS SageMaker vs Unleash
- AWS SageMaker vs Bun
- AWS SageMaker vs Cline
- AWS SageMaker vs Factory
- AWS SageMaker vs Humanloop
- AWS SageMaker vs Langfuse
- Windsurf vs Google Vertex AI
- Windsurf vs Azure Machine Learning
- Windsurf vs DataRobot
- Windsurf vs MLflow
- Windsurf vs Snowflake
- Windsurf vs TensorFlow
- Windsurf vs Comet ML
- Windsurf vs Jupyter
- Windsurf vs LangChain
- Windsurf vs Pinecone
- Windsurf vs Python
- Windsurf vs PyTorch
- Windsurf vs scikit-learn
- Windsurf vs Apache Spark MLlib
- Windsurf vs Weaviate
- Windsurf vs Weights & Biases
- Windsurf vs Alteryx
- Windsurf vs Anaconda
- Windsurf vs Cursor
- Windsurf vs Zed
- Windsurf vs Amp
- Windsurf vs Braintrust
- Windsurf vs Codacy
- Windsurf vs DeepSource
- Windsurf vs Devin
- Windsurf vs SonarQube Cloud
- Windsurf vs Augment Code
- Windsurf vs Baseten
- Windsurf vs Drizzle ORM
- Windsurf vs Flagsmith
- Windsurf vs Unleash
- Windsurf vs Bun
- Windsurf vs Cline
- Windsurf vs Factory
- Windsurf vs Humanloop
- Windsurf vs Langfuse