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ML platforms · October 2026 Edition

Azure Machine Learning vs Google Vertex AI

Five of fourteen models named Azure Machine Learning first on the direct prompt; two named Google Vertex AI. Both were named by all fourteen models and Azure Machine Learning carries 49 labels and Google Vertex AI 57, so the shares are not directly comparable.

Azure Machine Learning

accepted challenger

Named in two categories this edition.

Google Vertex AI

accepted challenger

Named in three categories this edition.

First-choice share21%9%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate14%19%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#4A position in a field of 13; printed, not drawn.
Labels4957A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Azure Machine Learning reading right to left. Rank and label count are printed, not drawn.Databricks Mosaic AI was named alongside these two in ten of the fourteen direct answers. Azure Machine Learning vs Databricks Mosaic AI · Azure Machine Learning vs Amazon SageMaker · Azure Machine Learning vs Google Colab

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.

By framing

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
Azure Machine LearningFirst choices, of fourteen modelsGoogle Vertex AI
Direct52
Paraphrase62
Comparative001 against Google Vertex AI
Budget-constrained111 against Azure Machine Learning · 1 against Google Vertex AI
Scale-constrained00
Negative006 against Azure Machine Learning · 9 against Google Vertex AI
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the October 2026 Edition, Azure Machine Learning and Google Vertex AI were named in the same answer 125 times, of the 159 answers naming Azure Machine Learning and the 173 naming Google Vertex AI. In those answers Google Vertex AI took the first choice fourteen times and Azure Machine Learning fifteen.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Azure Machine Learning and Google Vertex AI stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
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
Azure Machine Learning Google Vertex AI first choice named as an alternative argued againstblank: not namedEach cell is one answer, Azure Machine Learning on the left and Google Vertex AI on the right.

The direct prompt

The plain question, one answer per model, grouped by where Azure Machine Learning and Google Vertex AI stood in it.

Both were the first choice

1 of 14 modelsThe answer named them together, and the judge labeled each a first choice.
Perplexity SonarAzure Machine Learning, Google Vertex AI alternatives: Amazon Forecast, DataRobot

Azure Machine Learning first, Google Vertex AI an alternative

4 of 14 modelsGoogle Vertex AI was named in the answer but not as the choice, or not at all.
Grok 4.1 FastAzure Machine Learning alternatives: Amazon SageMaker, DataRobot, Databricks Mosaic AI, Google Vertex AI, H2O.ai
DeepSeek V4 FlashAzure Machine Learning alternatives: Amazon SageMaker, DataRobot, Databricks Mosaic AI, Dataiku, Google Vertex AI
Kimi K2Azure Machine Learning, Databricks Mosaic AI alternatives: Amazon SageMaker, Google Vertex AI
Muse Glimmer 30BAzure Machine Learning alternatives: Amazon SageMaker, Databricks Mosaic AI

Google Vertex AI first, Azure Machine Learning not the choice

1 of 14 modelsAzure Machine Learning was named in the answer but not as the choice, or not at all.
Mistral SmallDatabricks Mosaic AI, Google Vertex AI alternatives: Amazon SageMaker

Neither was the first choice, one was named

6 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Amazon SageMaker, Databricks Mosaic AI alternatives: Azure Machine Learning
GPT-5.4 miniDatabricks Mosaic AI alternatives: Amazon SageMaker, Google Vertex AI
Gemini 3.5 FlashPecan AI alternatives: Akkio, Azure Machine Learning, Dataiku, Google BigQuery ML, Snowflake Cortex AI
Qwen 3.7 FlashDataRobot alternatives: Azure Machine Learning, Databricks Mosaic AI, HubSpot Spot Intelligence, Salesforce Einstein, Snowflake Cortex AI
MiniMax M2.5DataRobot, Databricks Mosaic AI alternatives: Amazon SageMaker, Google Vertex AI
GPT-6 LunaDatabricks Mosaic AI alternatives: Azure Machine Learning, Google Vertex AI, SageMaker AI, Snowflake Cortex AI

Neither was named

2 of 14 modelsThe answer made no first choice from these two in this category.
Llama 4 Maverickno first choice
GLM 4.7 FlashXno first choice

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.

By buyer segment

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Google Vertex AI leads by fourteen points.
Google Vertex AI19%#1 of 14
Azure Machine Learning5%#5 of 14
The full small business standing →
Mid-marketThe figures above
The order flips: Azure Machine Learning leads at mid-market.
Azure Machine Learning21%#1 of 13
Google Vertex AI9%#4 of 13
The full mid-market standing →
Enterprise
Azure Machine Learning leads by seven points.
Azure Machine Learning11%#3 of 10
Google Vertex AI4%#7 of 10
The full enterprise standing →

What the models said about Azure Machine Learning

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.

“models suggesting caution or avoidance unless you have the necessary expertise and budget” Mistral Small · negative prompt · hard negative
“challenges such as data privacy, vendor lock-in, and cost unpredictability remain persistent concerns” Muse Glimmer 30B · negative prompt · soft negative
“Enterprise Cloud Platforms for Small Teams/Startups (e.g., SageMaker, Vertex AI, Azure ML)” Grok 4.1 Fast · negative prompt · soft negative
“Small team, tight budget, general ML: Azure Machine Learning or SageMaker AI are solid picks.” GPT-5.4 mini · budget prompt · first choice
“If you want a default pick and you're already Microsoft-centric, I'd choose Azure Machine Learning.” GPT-6 Luna · paraphrase prompt · first choice
“Azure Machine Learning and Google Vertex AI are the most broadly suitable platform choices” Perplexity Sonar · direct prompt · first choice

What the models said about Google Vertex AI

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.

“it is often recommended to avoid for small teams or startups due to complexity and cost concerns” Mistral Small · negative prompt · hard negative
“Some AI models advise against using this service for enterprise tasks until stability improves.” Llama 4 Maverick · negative prompt · hard negative
“be cautious if you are not already on Google Cloud, have a limited budget, or need a small-scale/simple setup” Perplexity Sonar · negative prompt · soft negative
“the most recommended MLOps platforms for training and deploying models are Vertex AI and Amazon SageMaker” Mistral Small · paraphrase prompt · first choice
“Azure Machine Learning and Google Vertex AI are the most broadly suitable platform choices” Perplexity Sonar · direct prompt · first choice
“I'd usually recommend Amazon SageMaker or Google Vertex AI as the best default choices” GPT-5.4 mini · paraphrase prompt · first choice
Also compared

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.