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Compare Google Cloud AI Hub and Vertex AI 
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At a Glance
Market Segments
Small-Business (41.7% of reviews)
Small-Business (41.1% of reviews)
Entry-Level Pricing
No pricing available
Pay As You Go Per Month
Google Cloud AI Hub
Star Rating
(12)4.3 out of 5
Market Segments
Small-Business (41.7% of reviews)
Pros & Cons
Not enough data
Entry-Level Pricing
No pricing available
Learn more about Google Cloud AI HubVertex AI
Star Rating
(591)4.3 out of 5
Market Segments
Small-Business (41.1% of reviews)
Pros & Cons
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 "AI Model Training Scalability" with a score of 8.5, allowing for efficient handling of large datasets, while Google Cloud AI Hub, with a score of 8.7, is noted for its robust "Model Training" capabilities, making it a strong contender for users focused on training complex models.
- Reviewers mention that Vertex AI's "AI Inference Speed" is rated at 8.6, which is crucial for real-time applications, whereas Google Cloud AI Hub's performance in this area is not explicitly rated, leading some users to feel uncertain about its speed in production environments.
- G2 users highlight that Vertex AI offers superior "Data Ingestion & Wrangling" features with a score of 8.3, which simplifies the data preparation process, while Google Cloud AI Hub's score of 7.9 indicates it may require more effort in this area, potentially impacting user experience.
- Users on G2 report that Vertex AI's "Pre-Built Algorithms" score of 8.4 provides a solid foundation for quick deployment, while Google Cloud AI Hub's higher score of 8.5 suggests it may offer a more extensive library of algorithms, appealing to users looking for variety and flexibility.
- Reviewers mention that Vertex AI's "AI GDPR and Regulatory Compliance" score of 8.6 is a strong point for businesses concerned about data privacy, while Google Cloud AI Hub's similar focus on compliance with a score of 8.2 indicates it may not be as robust in this critical area.
- Users say that Vertex AI's "AI Documentation Quality" is rated at 8.5, which is praised for its clarity and helpfulness, while Google Cloud AI Hub's documentation, although rated at 8.4, is perceived by some users as less comprehensive, potentially leading to a steeper learning curve.
Pricing
Entry-Level Pricing
Google Cloud AI Hub
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
Google Cloud AI Hub
No trial information availableVertex AI
Free Trial is available
Ratings
Meets Requirements
9.0
10
8.6
358
Ease of Use
8.3
10
8.2
367
Ease of Setup
Not enough data
8.1
290
Ease of Admin
Not enough data
7.9
141
Quality of Support
7.7
10
8.1
334
Has the product been a good partner in doing business?
Not enough data
8.2
135
Product Direction (% positive)
10.0
10
9.2
352
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
7.9
8
8.2
170
Model Development
8.3
9
8.4
202
7.6
9
7.9
179
8.5
9
8.4
200
8.7
9
8.5
202
Model Development
8.3
8
8.2
165
Machine/Deep Learning Services
8.7
9
8.2
200
8.0
9
8.4
196
8.5
9
8.2
195
8.3
9
8.2
178
Machine/Deep Learning Services
7.6
7
8.5
165
8.1
8
8.4
163
Deployment
8.0
9
8.2
193
8.3
9
8.3
194
8.7
9
8.5
193
Generative AI
7.9
8
8.3
102
8.1
8
8.2
102
7.3
8
8.1
103
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
8.1
34
Not enough data
7.8
34
Not enough data
7.7
34
Not enough data
7.8
34
Not enough data
8.4
34
Not enough data
7.8
34
Not enough data
7.9
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
8.9
23
Prompt Engineering - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
22
Not enough data
8.9
22
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
22
Model Garden - Large Language Model Operationalization (LLMOps)
Not enough data
9.2
22
Custom Training - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
22
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
22
Not enough data
8.7
21
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
21
Not enough data
8.8
21
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
8.7
21
Not enough data
9.0
21
Security - Large Language Model Operationalization (LLMOps)
Not enough data
9.1
22
Not enough data
8.9
22
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
8.9
22
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
Google Cloud AI Hub and Vertex AI are categorized as Data Science and Machine Learning Platforms
Unique Categories
Google Cloud AI Hub has no unique categories
Vertex AI is categorized as Large Language Model Operationalization (LLMOps), Generative AI Infrastructure, MLOps Platforms, Machine Learning, AI Agent Builders, and Low-Code Machine Learning Platforms
Reviews
Reviewers' Company Size
Google Cloud AI Hub
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
Financial Services
25.0%
Computer Software
25.0%
Computer & Network Security
16.7%
Telecommunications
8.3%
Program Development
8.3%
Other
16.7%
Computer Software
17.5%
Information Technology and Services
13.9%
Financial Services
7.0%
Retail
3.8%
Hospital & Health Care
3.4%
Other
54.3%
Alternatives
Discussions
What is Google Cloud AI Hub used for?
1 Comment
MN
Google Cloud AI Hub is a platform provided by Google Cloud that serves as a repository for machine learning (ML) and artificial intelligence (AI) assets....Read more
Google Cloud AI Hub has no more 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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