No more typing reviews! Try our Samantha, our new voice AI agent.

Azure OpenAI vs Gemini Enterprise Agent Platform comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Apr 23, 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
Gemini Enterprise Agent Pla...
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 (5th)
 

Mindshare comparison

As of June 2026, in the AI Development Platforms category, the mindshare of Azure OpenAI is 6.8%, down from 11.6% compared to the previous year. The mindshare of Gemini Enterprise Agent Platform is 8.0%, down from 12.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Mindshare Distribution
ProductMindshare (%)
Gemini Enterprise Agent Platform8.0%
Azure OpenAI6.8%
Other85.2%
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

"Azure's integration with OpenAI's GPT is beneficial as well, especially for text generation tasks."
"We can use the solution to implement our tasks and models quickly."
"The product is easy to integrate with our IT workflow."
"OpenAI's models are more mature than Watson's. They offer a wider range of features and provide richer outputs."
"It's very easy to set up and easy to use; there is no issue with that."
"Azure OpenAI is very easy to use instead of AWS services."
"Compared to other language models, OpenAI offers richer and more articulate responses."
"Two aspects I appreciate are the turnaround time and ease of use. As it's a managed service, the quick turnaround is beneficial, and the simple interface makes it easy to work with. Performance and scalability are also strong points since you can scale as needed."
"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."
"With just one single platform, Google Vertex AI platform, we can achieve everything; we need not switch over to multiple tools, multiple platforms, as everything can be accomplished through this one single platform for integration with existing workflows, systems, tools, and databases."
"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."
"It provides the most valuable external analytics."
"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."
"Vertex comes with inbuilt integration with GCP for data storage."
"The support is perfect and fantastic."
"The best feature of Google Vertex AI is the ease of use, along with the integration with the rest of the Google ecosystem and the way models can be made available outside Google through endpoints."
 

Cons

"Sometimes, the responses are repetitive."
"There is room for improvement in their support services."
"Azure could significantly benefit from including more LLM models apart from OpenAI, as I often need to switch clouds when a model doesn't meet my requirements."
"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."
"The dialogue manager needs to be improved."
"The UI could be a little easier."
"The solution can be improved by reducing the token cost so that consumption from the customer is on higher side."
"In terms of scalability, I would rate it nine for technical ability to expand. However, from a cost perspective, I would rate it five because it is too costly."
"Google Vertex AI is good in machine learning and AI, but it lacks optimization."
"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'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."
"We used AutoML feature for developing AI models automatically, but we are not comfortable with the performance of those models."
"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."
"The tool's documentation is not good. It is hard."
"It is not completely mature and needs some features and functions. The interface needs to be more user-friendly."
"I'm not sure if I have suggestions for improvement."
 

Pricing and Cost Advice

"The solution's pricing is normal worldwide but expensive in Turkey because Turkey's currency is different."
"I rate the product pricing six out of ten."
"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."
"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."
"According to the negotiations taking place and the contract, there is a need to make either monthly or yearly payments to use the solution."
"The cost is quite high and fixed."
"It's a token-based system, so you pay per token used by the model."
"Azure OpenAI is a bit more expensive than other services."
"The solution's pricing is moderate."
"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 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."
report
Use our free recommendation engine to learn which AI Development Platforms solutions are best for your needs.
899,258 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Computer Software Company
11%
Financial Services Firm
11%
Manufacturing Company
10%
Comms Service Provider
7%
Manufacturing Company
10%
Financial Services Firm
10%
Computer Software Company
8%
Comms Service Provider
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 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 primary use case for Azure OpenAI?
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 change...
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.
 

Also Known As

No data available
Vertex, Google Vertex AI
 

Overview

Find out what your peers are saying about Azure OpenAI vs. Gemini Enterprise Agent Platform and other solutions. Updated: April 2026.
899,258 professionals have used our research since 2012.