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Compare Azure OpenAI Service and Vertex AI 
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At a Glance
Market Segments
Enterprise (50.0% of reviews)
Small-Business (41.0% of reviews)
Entry-Level Pricing
No pricing available
Pay As You Go Per Month
Azure OpenAI Service
Star Rating
(19)4.7 out of 5
Market Segments
Enterprise (50.0% of reviews)
Entry-Level Pricing
No pricing available
Learn more about Azure OpenAI ServiceVertex AI
Star Rating
(593)4.3 out of 5
Market Segments
Small-Business (41.0% of reviews)
Entry-Level Pricing
Pay As You Go Per Month
Free Trial is available
Learn more about Vertex AISummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- Users report that Vertex AI excels in its AI High Availability feature, scoring 9.2, which reviewers mention ensures consistent performance and reliability for critical applications. In contrast, Azure OpenAI Service, while still strong, has a slightly lower score in this area, indicating room for improvement.
- Reviewers mention that Azure OpenAI Service shines in its AI Text Summarization capabilities, achieving a score of 8.7, which users say provides more nuanced and context-aware summaries compared to Vertex AI's score of 8.6. This makes Azure a better choice for users focused on content generation and summarization tasks.
- G2 users highlight the ease of deployment as a significant advantage for Azure OpenAI Service, with a score of 8.5, compared to Vertex AI's 8.4. Reviewers say that Azure's streamlined deployment process allows for quicker integration into existing workflows, making it more user-friendly for teams with limited technical resources.
- Users on G2 report that Vertex AI's model training capabilities are robust, with a score of 8.5, which reviewers mention is particularly beneficial for organizations looking to customize their AI models. Azure OpenAI Service matches this score, but users say Vertex AI offers more flexibility in training data management.
- Reviewers mention that Azure OpenAI Service has a slight edge in security features, particularly in AI Data Encryption, where it scored 9.2 compared to Vertex AI's 8.6. Users report that this makes Azure a more appealing option for businesses with stringent data protection requirements.
- Users say that Vertex AI's integration capabilities are strong, with a score of 8.5, particularly in AI API Support and Flexibility. However, reviewers mention that Azure OpenAI Service also performs well in this area, but some users feel that Vertex AI offers a more comprehensive set of tools for integrating with various data sources.
Pricing
Entry-Level Pricing
Azure OpenAI Service
No pricing availableVertex AI
Try Vertex AI Free
Pay As You Go
Per Month
New customers get $300 in free credits to spend on Vertex AI.
- A unified UI for the entire ML workflow
- Pre-trained APIs for vision, video, natural language, and more
- End-to-end integration for data and AI
Free Trial
Azure OpenAI Service
No trial information availableVertex AI
Free Trial is available
Ratings
Meets Requirements
9.0
16
8.6
359
Ease of Use
8.8
16
8.2
368
Ease of Setup
9.0
13
8.1
291
Ease of Admin
8.3
8
7.9
142
Quality of Support
8.5
16
8.1
335
Has the product been a good partner in doing business?
9.3
7
8.2
136
Product Direction (% positive)
10.0
15
9.2
353
Features by Category
Deployment
Not enough data
8.3
73
Not enough data
8.1
74
Not enough data
8.3
74
Not enough data
8.3
70
Not enough data
8.8
70
Deployment
Not enough data
8.4
73
Not enough data
8.3
72
Not enough data
8.4
71
Not enough data
8.5
71
Not enough data
8.7
69
Management
Not enough data
8.3
70
Not enough data
8.5
69
Not enough data
8.0
69
Not enough data
8.1
69
Operations
Not enough data
8.2
69
Not enough data
8.4
70
Not enough data
8.3
70
Management
Not enough data
8.1
68
Not enough data
8.4
69
Not enough data
8.3
68
Generative AI
Not enough data
8.2
34
Not enough data
8.4
34
System
Not enough data
8.2
170
Model Development
Not enough data
8.5
202
Not enough data
7.9
179
Not enough data
8.4
200
Not enough data
8.5
202
Model Development
Not enough data
8.3
165
Machine/Deep Learning Services
Not enough data
8.2
200
Not enough data
8.4
196
Not enough data
8.2
195
Not enough data
8.2
178
Machine/Deep Learning Services
Not enough data
8.5
165
Not enough data
8.5
163
Deployment
Not enough data
8.2
193
Not enough data
8.3
194
Not enough data
8.5
193
Generative AI
Not enough data
8.3
102
Not enough data
8.3
102
Not enough data
8.1
103
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
8.1
34
Not enough data
7.9
34
Not enough data
7.7
34
Not enough data
7.9
34
Not enough data
8.5
34
Not enough data
7.8
34
Not enough data
8.0
34
Scalability and Performance - Generative AI Infrastructure
Not enough data
8.9
28
Not enough data
8.6
28
Not enough data
8.5
28
Cost and Efficiency - Generative AI Infrastructure
Not enough data
8.2
28
Not enough data
7.8
28
Not enough data
7.9
28
Integration and Extensibility - Generative AI Infrastructure
Not enough data
8.4
28
Not enough data
8.1
28
Not enough data
8.3
28
Security and Compliance - Generative AI Infrastructure
Not enough data
8.6
28
Not enough data
8.5
28
Not enough data
8.9
28
Usability and Support - Generative AI Infrastructure
Not enough data
8.2
28
Not enough data
8.3
28
Integration - Machine Learning
Not enough data
8.5
67
Learning - Machine Learning
Not enough data
8.5
66
Not enough data
8.3
65
Not enough data
8.8
66
Large Language Model Operationalization (LLMOps)Hide 15 FeaturesShow 15 Features
Not enough data
9.0
23
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
23
Not enough data
9.0
23
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
23
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
9.3
23
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
23
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
9.2
22
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
23
Not enough data
8.7
22
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
22
Not enough data
8.9
22
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
22
Not enough data
9.1
22
Security - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
23
Not enough data
9.0
23
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
8.9
23
Customization - AI Agent Builders
Not enough data
8.5
27
Not enough data
7.6
27
Not enough data
8.3
26
Functionality - AI Agent Builders
Not enough data
8.1
27
Not enough data
7.3
27
Not enough data
8.2
26
Not enough data
7.2
27
Data and Analytics - AI Agent Builders
Not enough data
7.7
25
Not enough data
7.9
27
Not enough data
8.0
27
Integration - AI Agent Builders
Not enough data
8.7
27
Not enough data
8.0
27
Not enough data
8.0
27
Not enough data
7.5
27
Data Ingestion & Preparation - Low-Code Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Model Construction & Automation - Low-Code Machine Learning Platforms
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
Azure OpenAI Service and Vertex AI are categorized as Machine Learning
Unique Categories
Azure OpenAI Service has no unique categories
Reviews
Reviewers' Company Size
Azure OpenAI Service
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Vertex AI
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Information Technology and Services
38.9%
Computer Software
22.2%
Public Relations and Communications
5.6%
Oil & Energy
5.6%
Mental Health Care
5.6%
Other
22.2%
Computer Software
17.7%
Information Technology and Services
13.9%
Financial Services
7.0%
Retail
3.8%
Hospital & Health Care
3.4%
Other
54.2%
Alternatives
Discussions
Azure OpenAI Service has no discussions with answers
What is Google Cloud AI Platform used for?
2 Comments
KS
Google cloud AI Platform enables us to build Machine learning models, that works on any type and any size of data. Read more
What software libraries does cloud ML engine support?
2 Comments
JP
It's supporting approx all trending libraries.Read more
What is Google AI platform?
1 Comment
ZM
The Google AI Platform is a comprehensive set of tools and services provided by Google Cloud to develop, deploy, and manage artificial intelligence. It...Read more
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