# Amazon SageMaker: how AI models rank it, September 2026

IT AI Recommendation Index, September 2026 Edition. Named in 49 judge labels across 1 categories by 12 of 12 models. Page: https://it-ai-index.com/vendors/amazon-sagemaker/

## Standing by category

| Category | Share | Rank | Negative rate | Labels |
|---|---|---|---|---|
| ML platforms | 10% | 3 | 29% | 49 |

## What the models said for it

- "I'd recommend starting with your existing cloud provider—most often Amazon SageMaker (if on AWS), Google Vertex AI (GCP), or Azure Machine Learning (Azure)" (Grok 4.1 Fast, ML platforms)
- "I'd usually recommend starting with the managed ML service on whichever cloud you already use (SageMaker, Azure ML, or Vertex AI)" (DeepSeek V4 Flash, ML platforms)
- "Amazon SageMaker and Databricks are the top choices due to their scalability, integration, and comprehensive feature sets." (Mistral Small, ML platforms)
- "Broadest feature set, deep AWS integration ... Best for complex enterprise ML at scale. ~34% market share." (DeepSeek V4 Flash, ML platforms)

## And against it

- "Avoid these platforms if you are a small team, a startup, or just starting out." (GLM 4.7 FlashX, ML platforms)
- "SageMaker is notoriously complex, has a steep learning curve, and often drains mid-market budgets through hidden configuration costs" (Gemini 3.5 Flash, ML platforms)
- "may not be suitable for teams that prioritize open-source flexibility or operate in a multi-cloud environment due to vendor lock-in" (Llama 4 Maverick, ML platforms)
- "Cloud giants (SageMaker, Vertex AI, Azure ML): Secure but watch costs, lock-in, and misconfigs (e.g., exposed creds in Azure)." (Grok 4.1 Fast, ML platforms)

## Record

- Method: https://it-ai-index.com/methodology/
- Raw judge labels and full responses: https://it-ai-index.com/data/
- License: CC BY 4.0. Cite as IT AI Recommendation Index, September 2026 Edition, it-ai-index.com.