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Google Vertex AI vs OpenVINO comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 4, 2024

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

Google Vertex AI
Ranking in AI Development Platforms
2nd
Average Rating
8.4
Reviews Sentiment
7.4
Number of Reviews
10
Ranking in other categories
AI Infrastructure (1st)
OpenVINO
Ranking in AI Development Platforms
14th
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
5
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of April 2025, in the AI Development Platforms category, the mindshare of Google Vertex AI is 14.0%, down from 20.3% compared to the previous year. The mindshare of OpenVINO is 1.6%, down from 3.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms
 

Featured Reviews

Serge Dahdouh - PeerSpot reviewer
A user-friendly platform that automatizes machine learning techniques with minimal effort
We work with clients who request the implementation of a certain document into a chatbot. Because of the limited knowledge of AI, our task is to link that file to the ML and provide a platform that can work as a customer service. We previously used LangChain Phython, but now it is done through Vertex AI.
Mahender Reddy Pokala - PeerSpot reviewer
Improved model deployment on edge devices, but compatibility and scalability present challenges
I found OpenVINO ( /products/openvino-reviews )'s ability to convert custom models into its format particularly beneficial, as businesses sometimes require unique models specific to their use cases. Utilizing OpenVINO allowed me to run these custom models on devices directly, which I found quite impressive. Additionally, the Model Zoo offered by OpenVINO added value to the product.

Quotes from Members

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

Pros

"Vertex AI possesses multiple libraries, so it eliminates the need for extensive coding."
"The integration of AutoML features streamlines our machine-learning workflows."
"The most valuable features of the solution are that it is quite flexible, and some of the services are almost low-code, with no-code services, so it gives agents flexibility to build the use cases according to the operational needs."
"It provides the most valuable external analytics."
"Vertex comes with inbuilt integration with GCP for data storage."
"Google Vertex AI is an out-of-the-box and very easy-to-use solution."
"The monitoring feature is a true life-saver for data scientists. I give it a ten out of ten."
"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 inferencing and processing capabilities are quite beneficial for our requirements."
"The features for model comparison, the feature for model testing, evaluation, and deployment are very nice. It can work almost with all the models."
"The initial setup is quite simple."
"Intel's support team is very good."
"The runtime of OpenVINO is highly valuable for running different computer vision models."
 

Cons

"Google Vertex AI is good in machine learning and AI, but it lacks optimization."
"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 think the technical documentation is not readily available in the tool."
"The tool's documentation is not good. It is hard."
"It would be beneficial to have certain features included in the future, such as image generators and text-to-speech solutions."
"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."
"Both major systems, Azure and Google, are not yet stabilized, especially their customer support."
"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."
"It has some disadvantages because when you're working with very complex models, neural networks if OpenVINO cannot convert them automatically and you have to do a custom layer and later add it to the model. It is difficult."
"At this point, the product could probably just use a greater integration with more machine learning model tools."
"It would be great if OpenVINO could convert new models into its format more quickly."
"The model optimization is a little bit slow — it could be improved."
"Scalability is a challenge with OpenVINO, particularly when I try to connect multiple streams of input or run multiple edge devices consecutively."
 

Pricing and Cost Advice

"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."
"We didn't have to pay for any licensing with Intel OpenVINO. Everything is available on their site and easily downloadable for free."
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Top Industries

By visitors reading reviews
Computer Software Company
13%
Financial Services Firm
13%
Manufacturing Company
9%
Retailer
7%
Manufacturing Company
43%
Computer Software Company
8%
University
7%
Financial Services Firm
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

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?
I'm not sure if I have suggestions for improvement. Based on my comparison between the two, Vertex has various additional functionalities that Azure doesn't provide.
What is your experience regarding pricing and costs for OpenVINO?
The OpenVINO software itself is open source and not priced. However, I found edge devices, such as cameras, can be somewhat expensive, around $150.
What needs improvement with OpenVINO?
One improvement could be making OpenVINO less dependent on Intel-based processing chips. Expanding cross-platform compatibility, allowing it to work beyond Intel and its edge devices, would be bene...
What is your primary use case for OpenVINO?
I used OpenVINO ( /products/openvino-reviews ) for almost three years, starting in 2020. My initial use case involved attempting to connect or run models using quantization within cameras as edge d...
 

Overview

Find out what your peers are saying about Google Vertex AI vs. OpenVINO and other solutions. Updated: March 2025.
847,772 professionals have used our research since 2012.