Introducing G2.ai, the future of software buying.Try now
Compare SAS Model Manager and Vertex AI 
Featured Products
Sponsored
You’re seeing this ad based on the product’s relevance to this page. Sponsored content does not receive preferential treatment in any of G2’s ratings.
Lyzr.ai
Visit Website
Sponsored
You’re seeing this ad based on the product’s relevance to this page. Sponsored content does not receive preferential treatment in any of G2’s ratings.
ILUM
Visit Website
Sponsored
You’re seeing this ad based on the product’s relevance to this page. Sponsored content does not receive preferential treatment in any of G2’s ratings.
Burai
Visit Website
At a Glance
Market Segments
Enterprise (56.4% of reviews)
Small-Business (41.0% of reviews)
Entry-Level Pricing
No pricing available
Pay As You Go Per Month
SAS Model Manager
Star Rating
(69)4.6 out of 5
Market Segments
Enterprise (56.4% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about SAS Model ManagerVertex AI
Star Rating
(592)4.3 out of 5
Market Segments
Small-Business (41.0% 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 High Availability with a score of 9.2, indicating robust infrastructure support, while SAS Model Manager, although strong, scores lower in this area, suggesting it may not be as reliable for high-demand applications.
- Reviewers mention that Vertex AI's AI Inference Speed is rated at 8.6, which is crucial for real-time applications, whereas SAS Model Manager does not highlight this feature as prominently, leading to concerns about performance in time-sensitive scenarios.
- G2 users highlight Vertex AI's superior Language Flexibility with a score of 8.4, allowing for a broader range of programming languages, while SAS Model Manager's score of 7.7 indicates more limitations, which could affect user experience for diverse development teams.
- Users on G2 report that Vertex AI's Model Training Scalability is rated at 8.5, making it a better choice for organizations looking to scale their machine learning efforts, while SAS Model Manager's lower score suggests it may struggle with larger datasets or more complex models.
- Reviewers mention that Vertex AI offers a more intuitive Drag and Drop interface with a score of 8.1, which enhances user experience, while SAS Model Manager's lower score in this area indicates a steeper learning curve for new users.
- Users say that Vertex AI's AI Cost per API Call is rated at 8.0, which is competitive, but SAS Model Manager's pricing structure is noted to be less transparent, leading to potential cost concerns for users looking to manage budgets effectively.
Pricing
Entry-Level Pricing
SAS Model Manager
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
SAS Model Manager
Free Trial is available
Vertex AI
Free Trial is available
Ratings
Meets Requirements
8.3
12
8.6
359
Ease of Use
8.0
15
8.2
368
Ease of Setup
6.7
11
8.1
291
Ease of Admin
7.3
8
7.9
141
Quality of Support
8.8
12
8.1
335
Has the product been a good partner in doing business?
7.9
8
8.2
135
Product Direction (% positive)
9.1
13
9.2
353
Features by Category
Deployment
7.7
5
8.3
73
7.8
6
8.1
74
7.8
6
8.3
74
8.3
6
8.3
70
8.3
6
8.8
70
Deployment
7.2
6
8.4
73
7.5
6
8.3
72
8.1
6
8.4
71
8.1
6
8.5
71
8.1
6
8.7
69
Management
7.8
6
8.3
70
8.9
6
8.5
69
8.3
6
8.0
69
8.3
6
8.1
69
Operations
7.5
6
8.2
69
7.8
6
8.4
70
7.8
6
8.3
70
Management
7.8
6
8.1
68
8.9
6
8.4
69
8.3
6
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
8.4
202
Not enough data
7.9
179
Not enough data
8.4
200
Not enough data
8.5
202
Model Development
Not enough data
8.2
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
8.4
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
8.2
102
Not enough data
8.1
103
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
8.1
34
Not enough data
7.8
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
SAS Model Manager and Vertex AI are categorized as Machine Learning and MLOps Platforms
Unique Categories
SAS Model Manager has no unique categories
Reviews
Reviewers' Company Size
SAS Model Manager
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
Computer Software
61.8%
Hospital & Health Care
5.5%
Banking
5.5%
Public Safety
3.6%
Mechanical or Industrial Engineering
3.6%
Other
20.0%
Computer Software
17.5%
Information Technology and Services
13.9%
Financial Services
7.0%
Retail
3.8%
Hospital & Health Care
3.4%
Other
54.4%
Alternatives
Discussions
SAS Model Manager 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
Hunting for software insights?
With over 3 million reviews, we can provide the specific details that help you make an informed software buying decision for your business. Finding the right product is important, let us help.
