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Azure OpenAI vs Google Vertex AI comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Feb 8, 2026

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
2nd
Average Rating
7.8
Reviews Sentiment
6.4
Number of Reviews
36
Ranking in other categories
No ranking in other categories
Google Vertex AI
Ranking in AI Development Platforms
1st
Average Rating
8.2
Reviews Sentiment
6.3
Number of Reviews
15
Ranking in other categories
AI-Agent Builders (4th)
 

Mindshare comparison

As of March 2026, in the AI Development Platforms category, the mindshare of Azure OpenAI is 6.5%, down from 13.9% compared to the previous year. The mindshare of Google Vertex AI is 8.4%, down from 14.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Mindshare Distribution
ProductMindshare (%)
Google Vertex AI8.4%
Azure OpenAI6.5%
Other85.1%
AI Development Platforms
 

Featured Reviews

RC
AI Engineering Manager at a tech vendor with 10,001+ employees
Empowerment in regulatory content generation marred by inconsistency and hallucination issues
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 specific instructions and keep the temperature very low to avoid overly generative responses, ensuring we receive specific answers from the particular source document without deviation; however, the results can sometimes vary. 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 business provides the template instructions, and it should generate accordingly. While we have different prompts for various needs, sometimes it generates the correct results, and sometimes it does not, leading to inconsistency. For stability, based on the current model I am using, I would rate Azure OpenAI a 7 due to the ongoing hallucination issues.
Hamada Farag - PeerSpot reviewer
Technology Consultant at Beta Information Technology
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

"The product is easy to integrate with our IT workflow."
"Azure OpenAI's main use case for me involves defining solutions for incident remediation where AI provides intelligence to solve problems, perform root cause analysis, or triage incidents or changes."
"Generative AI or GenAI seems to be the best part of the solution."
"Its ability to understand and respond well to queries, including language translation for clients, is beneficial."
"The product saves a lot of time."
"It's very powerful. It allows users to query our documents using natural language and receive answers in the same way. This makes our product information much more accessible than traditional keyword-based search."
"You just have to write accurate prompts according to your requirements, and the solution gives very good results."
"OpenAI integrates seamlessly with the broader Microsoft Azure ecosystem, and that provides synergies with the other solutions. This integration makes it much easier to build solutions."
"It provides the most valuable external analytics."
"The most valuable feature we've found is the model garden, which allows us to deploy and use various models through the provided endpoints easily."
"The most useful function of Google Vertex AI for me is the ease of integration, as we can easily create a prompt and integrate it into our current system."
"The integration of AutoML features streamlines our machine-learning workflows."
"Google Vertex AI is better for deployment, configuration, delivery, licensing, and integration compared to other AI platforms."
"The support is perfect and fantastic."
"Vertex AI possesses multiple libraries, so it eliminates the need for extensive coding."
"The features I have found most valuable in Google Vertex AI are Gemini's large language models, which are currently among the best, and the vision tool of Gemini, which I consider quite good."
 

Cons

"In the next release, they could enhance the product's features for even greater usability and efficiency."
"Azure OpenAI is not available in all regions, and its technical support should be improved."
"The solution needs to accommodate smaller companies."
"Deployment was slightly complex for me to understand."
"I faced one issue with Azure OpenAI: My customer wanted more clarity on the pricing. They were not able to get proper answers from the documentation or the pricing calculator. I suggest that Microsoft maintain standardization in the pricing details published in the documentation and the pricing calculator."
"We encountered challenges related to question understanding."
"We are awaiting the new updates like multi-model capabilities."
"The solution's response is a bit slow sometimes."
"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."
"I think the technical documentation is not readily available in the tool."
"It would be beneficial to have certain features included in the future, such as image generators and text-to-speech solutions."
"We used AutoML feature for developing AI models automatically, but we are not comfortable with the performance of those models."
"I've noticed that using chat activity often presents a broader range of options and insights for a well-constructed question. Improving the knowledge base could be a key aspect for enhancement—expanding the information sources to enhance the generation process."
"It is not completely mature and needs some features and functions. The interface needs to be more user-friendly."
"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'm not sure if I have suggestions for improvement."
 

Pricing and Cost Advice

"Cost-wise, the product's price is a bit on the higher side."
"I rate the product pricing six out of ten."
"We started with monthly payments, but we plan to switch to yearly billing once we've stabilized our 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 solution's pricing depends on the services you will deploy."
"While the product meets our business requirements well, I consider it relatively expensive, especially for individual users like myself."
"The tool costs around 20 dollars a month."
"If you consider the long-term aspect of any project, Azure OpenAI is a costly solution."
"The solution's pricing is moderate."
"The price structure is very clear"
"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."
"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."
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Top Industries

By visitors reading reviews
Financial Services Firm
12%
Computer Software Company
11%
Manufacturing Company
10%
Comms Service Provider
6%
Computer Software Company
11%
Financial Services Firm
10%
Manufacturing Company
9%
Educational Organization
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business17
Midsize Enterprise1
Large Enterprise19
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise4
Large Enterprise7
 

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?
The customization option in Azure OpenAI is quite challenging because any customization must be done through the knowledge base since Azure OpenAI models cannot be trained. I must build a knowledge...
What is your experience regarding pricing and costs for Google Vertex AI?
I purchased Google Vertex AI directly from Google, as we are a partner of Google. I would rate the pricing for Google Vertex AI as low; the price is affordable.
What needs improvement with Google Vertex AI?
Google Vertex AI is quite complex to navigate and to start services with, as I need to do a lot of iterations to finally activate the services, which is one major flaw, although it is powerful. To ...
What is your primary use case for Google Vertex AI?
Google Vertex AI has been utilized for Vertex Pipelines. I have not utilized the pre-trained APIs in Google Vertex AI, as our deployment is primarily on AWS, and we use API calls.
 

Overview

Find out what your peers are saying about Azure OpenAI vs. Google Vertex AI and other solutions. Updated: March 2026.
884,873 professionals have used our research since 2012.