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Azure OpenAI vs Google Vertex AI comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Jul 27, 2025

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Azure OpenAI
Ranking in AI Development Platforms
1st
Average Rating
7.8
Reviews Sentiment
6.6
Number of Reviews
34
Ranking in other categories
No ranking in other categories
Google Vertex AI
Ranking in AI Development Platforms
2nd
Average Rating
8.4
Reviews Sentiment
6.7
Number of Reviews
12
Ranking in other categories
AI-Agent Builders (3rd)
 

Mindshare comparison

As of October 2025, in the AI Development Platforms category, the mindshare of Azure OpenAI is 9.4%, down from 18.1% compared to the previous year. The mindshare of Google Vertex AI is 10.3%, down from 19.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Market Share Distribution
ProductMarket Share (%)
Azure OpenAI9.4%
Google Vertex AI10.3%
Other80.3%
AI Development Platforms
 

Featured Reviews

Rafael Keller - PeerSpot reviewer
Creates effective scheduling agents with responsive AI capabilities
I am using it to create agents to schedule appointments for clinics and professionals in general. It serves both small and major companies. The primary use case involves creating agents Its ability to understand and respond well to queries, including language translation for clients, is…
Hamada Farag - PeerSpot reviewer
Customization and integration empower diverse AI applications
We are familiar with most Google Cloud services, particularly infrastructure services, storage, compute, AI tools, containerization, GCP containerization, and cloud SQL. We are familiar with approximately eighty percent of Google's services, primarily related to infrastructure, AI, containers, backup, storage, and compute. We are familiar with Gemini AI and Google Vertex AI, and we have completed some exercises and cases with our customers for Google AI. We use automation in machine learning. I work with a team where everyone has specific responsibilities. We have design and development processes in place. Based on my experience, I would rate Google Vertex AI a 9 out of 10.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"GPT was useful for our projects."
"The most valuable features include analyzing comments and preparing requests for customers, making emails easier and faster."
"The most crucial aspect is the conversational capability, where you can simply ask questions, and it provides answers based on your content and documents, particularly tailored to your specific environment."
"The product saves a lot of time."
"It is easy to integrate and develop a solution. Most customers are concerned about the security of their data and how cost-effective it is. We have developed some methodologies so that our customers will not be charged too much for these OpenAI services but will still get the same kind of performance and results. It's all developed on Azure, so customers also see its benefit."
"Our clients are interested in building knowledge bases, particularly in child welfare. In this domain, we focus on supporting caseworkers by compiling and organizing relevant information. This information is then stored in a database using a query. The database generates summaries and reminders for specific actions and even facilitates sending emails to parents or other relevant parties. The system's complexity is tailored to the specific needs of child welfare cases. Additionally, we're exploring opportunities to assist a healthcare organization. Specifically, we're working on streamlining the process of filling out forms required for insurance claims. This effort aims to ensure that hospitals can receive funding or payment for the care they provide."
"The product's initial setup phase was pretty easy."
"Azure OpenAI is useful for benchmarking products."
"Google Vertex AI is better for deployment, configuration, delivery, licensing, and integration compared to other AI platforms."
"The monitoring feature is a true life-saver for data scientists. I give it a ten out of ten."
"Vertex comes with inbuilt integration with GCP for data storage."
"It provides the most valuable external analytics."
"The integration of AutoML features streamlines our machine-learning workflows."
"The support is perfect and fantastic."
"Google Vertex AI is an out-of-the-box and very easy-to-use solution."
"We extensively utilize Google Cloud's Vertex AI platform for our machine learning workflows. Specifically, we leverage the IO branch for EDA data in Suresh Live Virtual, employing Forte IT for training machine learning models. The AI model registry in Vertex AI is crucial for cataloging and managing various versions of the models we develop. When it comes to deploying models, we rely on Google Cloud's AI Prediction service, seamlessly integrating it into our workflow for real-time predictions or streaming. For monitoring and tracking the outcomes of model development, we employ Vertex AI Monitoring, ensuring a comprehensive understanding of the model's performance and results. This integrated approach within Vertex AI provides a unified platform for managing, deploying, and monitoring machine learning models efficiently."
 

Cons

"There could be an ability to generate visual data, such as architecture diagrams."
"The product features themselves are fine. However, with Microsoft scaling the service so much, the support structure needs to keep pace. When solving complex issues, the process of interacting with Microsoft can be quite time-consuming."
"Maybe with the next release, the response will be more precise and more human-like."
"There are certain shortcomings with the product's scalability and support team where improvements are required."
"The main issue with Azure OpenAI is the inconsistency in output. We have a set template instruction, and it should generate within those parameters without any creativity because it's meant for regulatory authoring documents."
"The UI could be a little easier."
"We are awaiting the new updates like multi-model capabilities."
"The dialogue manager needs to be improved."
"The solution is stable, but it is quite slow. Maybe my data is too large, but I think that Google could improve Vertex AI's training time."
"I believe that Vertex AI is a robust platform, but its effectiveness depends significantly on the domain knowledge of the developer using it. While Vertex AI does offer support through the console UI in the Google Cloud environment, it is better suited for technical members who have a deeper understanding of machine learning concepts. The platform may be challenging for business process developers (BPDUs) who lack extensive technical knowledge, as it involves intricate customization and handling numerous parameters. Effectively utilizing Vertex AI requires not only familiarity with machine learning frameworks like TensorFlow or PyTorch but also a proficiency in Python programming. The complexity of these requirements might pose challenges for less technically oriented users, making it crucial to have a solid foundation in both machine learning principles and Python coding to extract the full value from Vertex AI. It would be beneficial to have a streamlined process where we can leverage the capabilities of Vertex AI directly through the BigQuery UI. This could involve functionalities such as creating machine learning models within the BigQuery UI, providing a more user-friendly and integrated experience. This would allow users to access and analyze data from BigQuery while simultaneously utilizing Vertex AI to build machine learning models, fostering a more cohesive and efficient workflow."
"I think the technical documentation is not readily available in the tool."
"It is not completely mature and needs some features and functions. The interface needs to be more user-friendly."
"Both major systems, Azure and Google, are not yet stabilized, especially their customer support."
"I'm not sure if I have suggestions for improvement."
"It takes a considerable amount of time to process, and I understand the technology behind why it takes this long, but this is something that could be reduced."
"It would be beneficial to have certain features included in the future, such as image generators and text-to-speech solutions."
 

Pricing and Cost Advice

"The cost is quite high and fixed."
"Regarding pricing and licensing, it's a bit complex due to the minimum purchase requirement for PTO units. We're evaluating the best approach between PTE and pay-as-you-go models. Our organization is cautious about committing to PTE due to the fixed bandwidth reservation, while pay-as-you-go doesn't offer enough flexibility. We're discussing these matters with legal teams to ensure compliance and data security."
"The tool costs around 20 dollars a month."
"According to the negotiations taking place and the contract, there is a need to make either monthly or yearly payments to use the solution."
"I'm uncertain about the licensing, specifically the pricing. This falls under the purview of other teams, particularly the sales teams. I am not informed about the pricing details."
"The pricing is acceptable, and it's delivering good value for the results and outcomes we need."
"The platform offers a flexible pricing model which depends on the features and capabilities we utilize."
"Cost-wise, the product's price is a bit on the higher side."
"The solution's pricing is moderate."
"The price structure is very clear"
"The Versa AI offers attractive pricing. With this pricing structure, I can leverage various opportunities to bring value to my business. It's a positive aspect worth considering."
"I think almost every tool offers a decent discount. In terms of credits or other stuff, every cloud provider provides a good number of incentives to onboard new clients."
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Top Industries

By visitors reading reviews
Computer Software Company
14%
Financial Services Firm
12%
Manufacturing Company
10%
Government
5%
Computer Software Company
14%
Financial Services Firm
10%
Manufacturing Company
9%
Educational Organization
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business15
Midsize Enterprise1
Large Enterprise18
By reviewers
Company SizeCount
Small Business4
Midsize Enterprise3
Large Enterprise6
 

Questions from the Community

What do you like most about Azure OpenAI?
The product is easy to integrate with our IT workflow.
What is your experience regarding pricing and costs for Azure OpenAI?
In terms of pricing for Azure OpenAI, I would rate it as average compared to Gemini. Currently, Gemini is becoming increasingly popular, which prompts leadership to consider a switch primarily due ...
What needs improvement with Azure OpenAI?
While it is good, we sometimes encounter hallucination issues, which is a significant concern. We are changing the prompt and fine-tuning it, but we still face some inconsistent behavior. We have s...
What do you like most about Google Vertex AI?
We extensively utilize Google Cloud's Vertex AI platform for our machine learning workflows. Specifically, we leverage the IO branch for EDA data in Suresh Live Virtual, employing Forte IT for trai...
What is your experience regarding pricing and costs for Google Vertex AI?
They have different pricing models like pay-as-you-go or subscription model, and total cost of ownership. It is comparatively cheaper than Azure.
What needs improvement with Google Vertex AI?
Google Vertex AI is one of the best in the market, followed by Azure AI. It can be rated at eight or nine out of ten. It is not completely mature and needs some features and functions. The interfac...
 

Overview

Find out what your peers are saying about Azure OpenAI vs. Google Vertex AI and other solutions. Updated: September 2025.
868,706 professionals have used our research since 2012.