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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 OpenAI is useful for benchmarking products."
"Azure OpenAI is easy to use because the endpoints are created, and we just need to pass our parameters and info."
"Azure OpenAI is used as chat services, allowing me to replace human tasks with analytical capabilities."
"The most valuable feature is the ALM."
"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."
"The product is easy to integrate with our IT workflow."
"Azure OpenAI has significantly reduced costs and increased efficiency in tasks such as aggressive testing of systems to avoid anomalies and trust issues."
"Azure's integration with OpenAI's GPT is beneficial as well, especially for text generation tasks."
"The integration of AutoML features streamlines our machine-learning workflows."
"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."
"Google Vertex AI is better for deployment, configuration, delivery, licensing, and integration compared to other AI platforms."
"Vertex AI possesses multiple libraries, so it eliminates the need for extensive coding."
"It provides the most valuable external analytics."
"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 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 support is perfect and fantastic."
 

Cons

"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."
"Azure OpenAI is not an optimized tool yet, making it one of its shortcomings where improvements are required."
"I noticed there are no instructional videos or guides on the network portal for initial configurations. There is limited information available, and this is a concern for me. I would like to see more resources and guides to address these issues."
"Sometimes, the responses are repetitive."
"The fine-tuning of models with the use of Azure OpenAI is an area with certain shortcomings currently, and it can be considered for improvement in the future."
"The product must improve its dashboards."
"The solution can be improved by reducing the token cost so that consumption from the customer is on higher side."
"Latency performance is a major part. And I'm seeking support for multiple models that handle text, images, videos, and voice. I'm from India, and I'm looking for more support in Indian languages. There are 18 official languages and many more unofficial. We need support for these languages, especially in voice moderation, which is not yet available."
"Both major systems, Azure and Google, are not yet stabilized, especially their customer support."
"Google can improve Google Vertex AI in terms of analysis and accuracy. When passing a very large context, instead of receiving vague responses, it would be better if the system could prompt users not to pass overly large prompts and provide clearer guidance on how to fine-tune Gemini for specific use cases."
"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."
"It would be beneficial to have certain features included in the future, such as image generators and text-to-speech solutions."
"Google Vertex AI is good in machine learning and AI, but it lacks optimization."
"The tool's documentation is not good. It is hard."
"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."
"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."
 

Pricing and Cost Advice

"The cost is quite high and fixed."
"If you consider the long-term aspect of any project, Azure OpenAI is a costly solution."
"The pricing is acceptable, and it's delivering good value for the results and outcomes we need."
"The solution's pricing depends on the services you will deploy."
"We started with monthly payments, but we plan to switch to yearly billing once we've stabilized our solution."
"It's a token-based system, so you pay per token used by the model."
"Cost-wise, the product's price is a bit on the higher side."
"The licensing is interaction-based, meaning transactional. It's reasonably priced for now."
"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."
"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."
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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.
899,283 professionals have used our research since 2012.