2026 Best Software Awards are here!See the list
Compare AWS Bedrock and Vertex AI 
At a Glance
Market Segments
Enterprise (39.6% of reviews)
Small-Business (41.6% of reviews)
Entry-Level Pricing
No pricing available
Pay As You Go Per Month
AWS Bedrock
Star Rating
(48)4.3 out of 5
Market Segments
Enterprise (39.6% of reviews)
Pros & Cons
Entry-Level Pricing
No pricing available
Learn more about AWS BedrockVertex AI
Star Rating
(644)4.3 out of 5
Market Segments
Small-Business (41.6% 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.
- G2 reviewers report that Vertex AI excels in managing complex machine learning workflows, with users appreciating its ability to centralize the entire ML lifecycle. One user highlighted how it simplifies everything from data preparation to deployment, making it a robust choice for those looking to streamline their processes.
- Users say that AWS Bedrock offers a significant advantage with its unified API, allowing for easy switching between different models like Anthropic Claude 3.5 and Meta Llama 3. This flexibility is particularly beneficial for teams looking to future-proof their applications without extensive reconfiguration.
- Reviewers mention that Vertex AI's integration with Google Cloud is seamless, which enhances the overall user experience. Users have noted that this integration simplifies the management of ML projects, making it easier to deploy and monitor models effectively.
- According to verified reviews, AWS Bedrock's setup process is praised for its simplicity, with users finding it easy to get started. One reviewer specifically noted the great selection of foundational models available, which can be a strong selling point for teams needing quick access to various AI capabilities.
- G2 reviewers highlight that while Vertex AI has a slightly lower score in ease of setup compared to AWS Bedrock, its comprehensive features for model training and deployment make it a preferred choice for users who prioritize a full-fledged ML platform over initial setup speed.
- Users report that both platforms have their strengths in support and documentation, but AWS Bedrock edges out slightly in user satisfaction regarding support quality. Reviewers have noted that AWS's additional services provide good support, which can be crucial for teams relying on a broader ecosystem.
Pricing
Entry-Level Pricing
AWS Bedrock
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
AWS Bedrock
No trial information availableVertex AI
Free Trial is available
Ratings
Meets Requirements
8.7
48
8.6
385
Ease of Use
8.1
48
8.2
396
Ease of Setup
8.4
47
8.1
318
Ease of Admin
9.0
17
7.9
147
Quality of Support
8.5
47
8.1
360
Has the product been a good partner in doing business?
8.5
16
8.3
141
Product Direction (% positive)
9.3
47
9.2
379
Features by Category
Deployment
Not enough data
8.4
76
Not enough data
8.1
77
Not enough data
8.3
76
Not enough data
8.4
76
Not enough data
8.8
74
Deployment
Not enough data
8.5
75
Not enough data
8.3
73
Not enough data
8.4
72
Not enough data
8.6
74
Not enough data
8.7
71
Management
Not enough data
8.2
71
Not enough data
8.5
72
Not enough data
8.0
71
Not enough data
8.1
70
Operations
Not enough data
8.2
70
Not enough data
8.5
71
Not enough data
8.3
71
Management
Not enough data
8.1
69
Not enough data
8.4
72
Not enough data
8.3
70
Generative AI
Not enough data
8.3
36
Not enough data
8.5
36
System
Not enough data
8.2
173
Model Development
Not enough data
8.5
207
Not enough data
7.9
181
Not enough data
8.4
205
Not enough data
8.5
209
Model Development
Not enough data
8.2
167
Machine/Deep Learning Services
Not enough data
8.3
203
Not enough data
8.5
202
Not enough data
8.2
200
Not enough data
8.3
181
Machine/Deep Learning Services
Not enough data
8.5
167
Not enough data
8.5
166
Deployment
Not enough data
8.3
211
Not enough data
8.3
200
Not enough data
8.6
206
Generative AI
Not enough data
8.3
109
Not enough data
8.3
105
Not enough data
8.1
105
Agentic AI - Data Science and Machine Learning Platforms
Not enough data
8.2
37
Not enough data
7.8
37
Not enough data
7.7
38
Not enough data
7.9
35
Not enough data
8.5
37
Not enough data
7.5
36
Not enough data
7.7
36
Scalability and Performance - Generative AI Infrastructure
9.1
16
9.0
31
8.6
14
8.7
32
8.0
15
8.6
31
Cost and Efficiency - Generative AI Infrastructure
7.8
17
8.0
34
8.6
16
7.7
31
7.9
14
8.1
30
Integration and Extensibility - Generative AI Infrastructure
8.6
14
8.5
30
9.0
16
8.3
32
8.4
16
8.5
31
Security and Compliance - Generative AI Infrastructure
8.6
14
8.7
30
8.8
15
8.3
32
8.5
14
8.9
30
Usability and Support - Generative AI Infrastructure
7.4
16
8.2
31
7.7
14
8.5
31
Integration - Machine Learning
Not enough data
8.5
68
Learning - Machine Learning
Not enough data
8.5
66
Not enough data
8.3
65
Not enough data
8.8
66
Prompt Engineering - Large Language Model Operationalization (LLMOps)
8.0
5
8.8
24
7.3
5
9.0
24
Inference Optimization - Large Language Model Operationalization (LLMOps)
Not enough data
8.8
22
Model Garden - Large Language Model Operationalization (LLMOps)
8.7
5
9.3
25
Custom Training - Large Language Model Operationalization (LLMOps)
7.7
5
9.1
24
Application Development - Large Language Model Operationalization (LLMOps)
Not enough data
9.2
23
Model Deployment - Large Language Model Operationalization (LLMOps)
Not enough data
9.0
23
8.3
5
8.7
22
Guardrails - Large Language Model Operationalization (LLMOps)
Not enough data
8.7
23
Not enough data
8.9
22
Model Monitoring - Large Language Model Operationalization (LLMOps)
Not enough data
8.7
21
Not enough data
9.1
22
Security - Large Language Model Operationalization (LLMOps)
9.0
5
9.1
22
Not enough data
9.0
23
Gateways & Routers - Large Language Model Operationalization (LLMOps)
Not enough data
8.9
22
Customization - AI Agent Builders
7.9
7
8.6
28
7.6
7
7.6
27
7.7
8
8.3
26
Functionality - AI Agent Builders
7.5
8
8.1
27
7.4
7
7.3
27
7.4
7
8.2
26
8.1
7
7.2
27
Data and Analytics - AI Agent Builders
8.1
7
7.8
26
8.1
7
7.9
27
9.3
7
8.1
28
Integration - AI Agent Builders
8.3
7
8.8
28
8.3
7
8.2
29
7.9
7
8.1
28
7.5
6
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
AWS Bedrock and Vertex AI are categorized as Large Language Model Operationalization (LLMOps), Generative AI Infrastructure, and AI Agent Builders
Unique Categories
AWS Bedrock has no unique categories
Vertex AI is categorized as MLOps Platforms, Data Science and Machine Learning Platforms, Machine Learning, and Low-Code Machine Learning Platforms
Reviews
Reviewers' Company Size
AWS Bedrock
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
20.8%
Computer Software
18.8%
Financial Services
8.3%
Consulting
6.3%
Retail
4.2%
Other
41.7%
Computer Software
17.9%
Information Technology and Services
14.3%
Financial Services
6.9%
Retail
3.6%
Hospital & Health Care
3.3%
Other
54.1%
Alternatives
Discussions
AWS Bedrock has no discussions with answers
What is Google Cloud AI Platform used for?
3 Comments
AO
Vertex AI is Google Cloud’s managed machine learning platform. It’s used to build, train, and deploy ML models at scale. It unifies data, AutoML, and custom...Read more
What software libraries does cloud ML engine support?
3 Comments
AO
Cloud ML Engine (now part of Vertex AI) supports popular ML frameworks and libraries such as TensorFlow, PyTorch, Scikit‑learn, and XGBoost. This flexibility...Read more
What is Google AI platform?
2 Comments
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.
