Vertex AI vs SageMaker vs Azure ML (2026)

We compare the three major ML platforms — Vertex AI (GCP) / SageMaker (AWS) / Azure ML — in depth. Beyond traditional MLOps comparisons, the current selection criteria have shifted to Gen AI integration, cost, and ecosystem fit.

Key Comparison Table

Item	Vertex AI	SageMaker	Azure ML / AI Foundry
In-house LLM	Gemini 2.0 Flash/Pro/Ultra	—	—
OpenAI	—	—	Azure OpenAI (GPT-4o / o1)
Anthropic Claude	Excellent	Excellent (Bedrock)	—
Meta Llama / Mistral	Excellent	Excellent (Bedrock)	Good
Custom AI Chips	TPU v5p / Trillium	Trainium 2 / Inferentia 2	—
AutoML	Tables / Vision / Video / NL / Forecasting	Autopilot (tabular-focused)	AutoML (tabular + NL + Vision)
Pipelines	Vertex AI Pipelines (KFP v2)	SageMaker Pipelines	Azure ML Pipelines (MLflow)
Feature Store	Vertex FS (BQ-based, new in 2024)	SageMaker FS	Azure ML Feature Store
Model Registry	Excellent	Excellent	Excellent
Monitoring	Excellent	Excellent	Excellent

Gen AI Model Comparison

Model	Vertex AI	SageMaker / Bedrock	Azure
Gemini	Excellent (Flash $0.075/M tok)	—	—
GPT-4o	—	—	Excellent ($2.50/M tok)
Claude Opus 4 / Sonnet 4	Excellent	Excellent	—
Llama 3.3	Excellent	Excellent	Good
Mistral Large	Excellent	Excellent	Excellent
Imagen 3 (image generation)	Excellent	Stable Diffusion / Titan Image	DALL-E 3
Veo (video generation)	Excellent	—	Sora (limited)

Pricing Example (n1-standard-4 inference + GPU L4)

Item	Vertex AI	SageMaker	Azure ML
n1-standard-4 + L4	~$0.81/h	~$0.96/h (ml.g6.xlarge)	~$0.99/h (NC4ads T4 v3)
Endpoint (HTTP)	vCPU hours	vCPU hours	vCPU hours
Batch Prediction	vCPU hours (cheaper)	vCPU hours	vCPU hours

MLOps Component Comparison

Vertex AI: KFP v2 OSS compatible, TFX, Cloud Build integration, direct BigQuery connectivity
SageMaker: SageMaker Studio (IDE), Pipelines, Clarify (explainability), Inference Recommender
Azure ML: MLflow native, Responsible AI Toolkit, Designer (drag-and-drop)

Selection Flow

Data platform is BigQuery → Vertex AI (Feature Store is BQ-based)
GPT-4 / Azure OpenAI required → Azure ML / AI Foundry
AWS integration + Claude / Llama → SageMaker + Bedrock
Minimize LLM cost → Vertex AI (Gemini Flash $0.075/M tok)
Video generation → Vertex AI (Veo)
OSS compatibility (MLflow / KFP) → Vertex AI Pipelines / Azure ML
Tabular AutoML → all three support it

Strengths and Weaknesses Summary

Vertex AI: Gemini + TPU + BigQuery integration, strongest Gen AI model catalog
SageMaker: Deepest AWS ecosystem integration, the most services, and the longest track record
Azure ML: Exclusive Azure OpenAI access, rich Responsible AI tooling, and Microsoft 365 integration

Which should I choose: Vertex AI, SageMaker, or Azure ML?

GCP data + Gen AI focus → Vertex AI. AWS ecosystem + breadth of services → SageMaker. Azure integration + GPT-4 required → Azure ML / AI Foundry.

Which platform has the strongest Gen AI integration?

Vertex AI is strongest with Gemini + Anthropic Claude + Llama + Imagen. SageMaker counters with Bedrock integration, and Azure with Azure OpenAI (GPT-4o / o1).

Which platform has the most complete MLOps features?

All three provide Pipelines, Model Registry, Monitoring, and Feature Store. Vertex AI = KFP OSS compatible, SageMaker = the most services, Azure ML = MLflow native.

Which AutoML offering is strongest?

Vertex AutoML covers the broadest scope (images, video, NL, tabular). SageMaker Autopilot focuses on tabular + explainability. Azure ML AutoML focuses on tabular + Responsible AI.

What about GPU / TPU options?

Vertex AI offers NVIDIA H100/L4 + TPU v5p/Trillium (the strongest dedicated AI chip lineup). SageMaker offers P5/G6 + Trainium/Inferentia. Azure ML offers ND H100/H200 v5.

Which platform is cheapest?

It depends on base infrastructure pricing. Vertex AI's serverless Endpoint and TPU are the cheapest candidates for large-scale ML training. Inference pricing is roughly comparable across the three.

Are training and inference separated?

All three platforms support this. Vertex AI Endpoint, SageMaker Endpoint, and Azure ML Endpoint share the same specification, with Online / Batch / Streaming inference modes.

What certifications are available?

Vertex AI = PMLE ($200). SageMaker = AWS MLA-C01 ($300) + Specialty (being retired). Azure ML = AI-102 ($165) + DP-100 ($165).

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NicheeLab Editorial Team

NicheeLab editorial team focused on data engineering and cloud certification learning. Content is structured around practical study needs and official exam domains.

Vertex AI vs SageMaker vs Azure ML: Complete MLOps Platform Comparison