One of fourteen models named Amazon SageMaker first on the direct prompt; two named Snowflake Cortex AI. Amazon SageMaker was named by fourteen of the fourteen models and Snowflake Cortex AI by nine and Amazon SageMaker carries 67 labels and Snowflake Cortex AI 15, so the shares are not directly comparable.
Named in two categories this edition.
Named in one category this edition.
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the ML platforms page.
Across every category in the November 2026 Edition, Amazon SageMaker and Snowflake Cortex AI were named in the same answer twenty-nine times, of the 198 answers naming Amazon SageMaker and the 32 naming Snowflake Cortex AI. In those answers Snowflake Cortex AI took the first choice one time and Amazon SageMaker three.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | ||||||
| GPT-5.4 mini | ||||||
| Gemini 3.5 Flash | ||||||
| Perplexity Sonar | ||||||
| Grok 4.20 | ||||||
| Mistral Small | ||||||
| DeepSeek V4 Flash | ||||||
| Llama 4 Maverick | ||||||
| Qwen 3.7 Flash | ||||||
| Kimi K2 | ||||||
| GLM 4.7 FlashX | ||||||
| MiniMax M2.5 | ||||||
| GPT-6 Luna | ||||||
| Muse Glimmer 30B |
Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Avoid heavy enterprise tools like Databricks or full SageMaker unless you have specific needs” Grok 4.20 · budget prompt · hard negative
“SageMaker, Vertex AI, and Azure ML can simplify operations, but their proprietary APIs, registries, pipelines, and deployment workflows can create vendor lock-in.” Perplexity Sonar · negative prompt · soft negative
“Heavily Integrated Cloud Platforms (e.g., AWS SageMaker, Google Vertex AI, Microsoft Azure ML): Why cautious? Strong vendor lock-in” Grok 4.20 · negative prompt · soft negative
“Start with SageMaker AI, Gemini Enterprise Agent Platform, or Azure Machine Learning if you're committed to that cloud.” GPT-6 Luna · comparative prompt · first choice
“Azure Machine Learning or AWS SageMaker provide the best balance of features, scalability, and cost-effectiveness” GLM 4.7 FlashX · direct prompt · first choice
“recommend a managed cloud-native platform—usually AWS SageMaker AI, Azure Machine Learning, or Google Vertex AI” Perplexity Sonar · paraphrase prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“Databricks / Snowflake ML ... compute costs scale aggressively” Gemini 3.5 Flash · negative prompt · soft negative
“I'd recommend starting with Snowflake Cortex AI or Databricks as they offer the best balance of capabilities” MiniMax M2.5 · direct prompt · first choice
“Azure Machine Learning and Snowflake Cortex AI are the top choices” Mistral Small · direct prompt · first choice
“lists Snowflake Cortex AI as a strong fit for firms already standardised on Snowflake” Muse Glimmer 30B · direct prompt · alternative
Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.