Google Vertex AI vs OpenVINO comparison

Google and Intel are both solutions in the AI Development Platforms category. Google is ranked #1 with an average rating of 8.4, while Intel is ranked #12 with an average rating of 7.3. Google holds a 11.1% mindshare in AIDP, compared to Intel’s 1.7% mindshare. Additionally, 100% of Google users are willing to recommend the solution, compared to 100% of Intel users who would recommend it.

Google Vertex AI

Read 12 Google Vertex AI reviews

8,399 Views
7,559 Comparison Views

100% willing to recommend

OpenVINO

Read 7 OpenVINO reviews

1,731 Views
1,731 Comparison Views

100% willing to recommend

Google Vertex AI

OpenVINO

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 4, 2024

OpenVINO and Google Vertex AI are competing in the AI tools market aimed at streamlined AI model deployment and optimization. Google Vertex AI seems to have the upper hand due to its comprehensive feature set tailored for varied machine learning needs, justifying its higher price point to many users.

Features:OpenVINO focuses on optimizing deep learning models, particularly for efficient execution on Intel hardware, targeting computer vision tasks. Google Vertex AI offers robust integration capabilities with a range of Google Cloud services, making it suitable for end-to-end machine learning workflows. OpenVINO's efficiency on Intel hardware is a major draw for those in such ecosystems. Google Vertex AI supports a wide array of machine learning needs, making it versatile for diverse business applications.

Ease of Deployment and Customer Service:Google Vertex AI provides a seamless deployment experience through Google Cloud's extensive infrastructure and support resources. In contrast, OpenVINO requires more in-depth technical knowledge for setup, focusing on Intel-centric solutions with specialized support.

Pricing and ROI:OpenVINO appeals to those looking for lower initial costs, especially for businesses already invested in Intel ecosystems. Google Vertex AI, despite its higher setup and operational expenses, offers significant ROI for enterprises seeking scalable AI solutions with comprehensive Google service integration.

To learn more, read our detailed Google Vertex AI vs. OpenVINO Report (Updated: July 2025).

Buyer's Guide

Google Vertex AI vs. OpenVINO

July 2025

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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

1st

Average Rating

8.4

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

AI Infrastructure (1st)

OpenVINO

Ranking in AI Development Platforms

12th

Average Rating

8.2

Reviews Sentiment

6.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of August 2025, in the AI Development Platforms category, the mindshare of Google Vertex AI is 11.1%, down from 20.9% compared to the previous year. The mindshare of OpenVINO is 1.7%, down from 2.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

AI Development Platforms

Featured Reviews

Hamada Farag

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.

Read full review

Mahender Reddy Pokala

AI Developer at University of Chicago

Improved model deployment on edge devices, but compatibility and scalability present challenges

I found OpenVINO'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.

Read full review

Quotes from Members

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

Pros

"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."

"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."

"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 support is perfect and fantastic."

"Google Vertex AI is better for deployment, configuration, delivery, licensing, and integration compared to other AI platforms."

"Vertex comes with inbuilt integration with GCP for data storage."

"It provides the most valuable external analytics."

More Google Vertex AI pros

"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 inferencing and processing capabilities are quite beneficial for our requirements."

"The benefit from using OpenVINO is that NVIDIA is dominating the market of GPUs and they set the price, so if I am able to run an LLM doing inference in commodity hardware, I am saving costs."

"Intel's support team is very good."

"The initial setup is quite simple."

"The runtime of OpenVINO is highly valuable for running different computer vision models."

Cons

"It is not completely mature and needs some features and functions. The interface needs to be more user-friendly."

"I think the technical documentation is not readily available in the tool."

"Google Vertex AI is good in machine learning and AI, but it lacks optimization."

"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."

"Both major systems, Azure and Google, are not yet stabilized, especially their customer support."

"It would be beneficial to have certain features included in the future, such as image generators and text-to-speech solutions."

"The tool's documentation is not good. It is hard."

"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."

More Google Vertex AI cons

"I think that it's not properly designed for scalability. It's designed for other purposes, specifically to be able to use Intel hardware and run inference using generative models or deep learning models in Intel hardware."

"The model optimization is a little bit slow — it could be improved."

"At this point, the product could probably just use a greater integration with more machine learning model tools."

"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."

"It would be great if OpenVINO could convert new models into its format more quickly."

"I couldn't get it to run on my Raspberry Pi 4 because the software packages to download were no longer available."

"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 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."

"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

14%

Financial Services Firm

11%

Manufacturing Company

Educational Organization

Manufacturing Company

39%

Financial Services Firm

Comms Service Provider

University

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...

See all answers

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.

See all answers

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...

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What is your experience regarding pricing and costs for OpenVINO?

The pricing of OpenVINO is reasonable.

See all answers

What needs improvement with OpenVINO?

I have heard good things about OpenVINO. It doesn't consume much current for external GPU usage. However, it has some downsides because I couldn't get it to run on my Raspberry Pi 4. While not spec...

See all answers

What is your primary use case for OpenVINO?

I wanted to use OpenVINO for my Raspberry Pi to analyze my sleep with a night vision camera and to improve GPU performance on my Raspberry Pi. I would have used OpenVINO's Model Optimizer feature t...

See all answers

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Compared 5% of the time

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TensorFlow vs OpenVINO

Compared 54% of the time

PyTorch vs OpenVINO

Compared 24% of the time

Azure OpenAI vs OpenVINO

Compared 9% of the time

Amazon SageMaker vs OpenVINO

Compared 4% of the time

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Product Reports

Buyer's Guide

Google Vertex AI

August 2025

Download Google Vertex AI product report

Buyer's Guide

OpenVINO

August 2025

Download OpenVINO product report

Overview

Build, deploy, and scale ML models faster, with pre-trained and custom tooling within a unified artificial intelligence platform.

Google

OpenVINO toolkit quickly deploys applications and solutions that emulate human vision. Based on Convolutional Neural Networks (CNNs), the toolkit extends computer vision (CV) workloads across Intel hardware, maximizing performance. The OpenVINO toolkit includes the Deep Learning Deployment Toolkit (DLDT).

Intel

Buyer's Guide

Google Vertex AI vs. OpenVINO

July 2025

Free Report: Google Vertex AI vs. OpenVINO

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