Google Cloud AI Platform vs IBM Watson Machine Learning comparison

Google Cloud AI Platform vs. IBM Watson Machine Learning

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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 Cloud AI Platform

Ranking in AI Development Platforms

7th

Average Rating

7.8

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

IBM Watson Machine Learning

Ranking in AI Development Platforms

11th

Average Rating

8.0

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of February 2025, in the AI Development Platforms category, the mindshare of Google Cloud AI Platform is 4.9%, down from 7.0% compared to the previous year. The mindshare of IBM Watson Machine Learning is 1.9%, down from 2.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

AI Development Platforms

Featured Reviews

Vipul-Kumar

CTO at Intelli AI LLC

An AI platform AI Platform to train your machine learning models at scale, to host your trained model in the cloud, and to use your model to make predictions about new data

I think it's the it it also has has evolved quite a bit over the last few years, and Google Cloud folks have been getting, more and more services. But I think from a improvement standpoint, so maybe they can look at adding more algorithms, so adding more AI algorithms to their suite.

Read full review

Anurag Mayank

Manager at Maruti Suzuki India Limited

A highly efficient solution that delivers the desired results to its users

I had not considered how the solution could be improved because I was focused on how it was helping me to solve my issues. If I consider how we want to use it in our organization, certain areas of improvement can be addressed. For instance, we want to use it with Generative AI, not like ChatGPT, but in a way intended for industrial use. It would be beneficial to incorporate more AI into the solution.

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

"On GCP, we are exposing our API services to our clients so that they send us their information. It can be single individual records or it can be a batch of their clients."

"Since the model could be trained in just a couple of hours and deploying it took only a few minutes, the entire process took less than an hour."

"I have seen measurable benefits from Google Cloud AI Platform."

"The solution is able to read 90% of the documents correctly with a 10% error rate."

"Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture."

"A range of a a wide range of algorithms, EIM voice mails, which can be plugged in right away into your solution into into into our solution, and then have platform that provides know, to to come up with an operational solution really quick."

"The feedback left about these tools was really helpful and informative for us"

"The platform's Google Vision API is particularly valuable."

More Google Cloud AI Platform pros

"It is has a lot of good features and we find the image classification very useful."

"Scalability-wise, I rate the solution ten out of ten."

"I was particularly interested in trying the AutoML feature to see how it handles data and proposes new models. The variety of models it provides is impressive."

"We can enable and change developer productivity with artificial intelligence-recommended code based on natural language input or exciting source code."

"The solution is very valuable to our organization due to the fact that we can work on it as a workflow."

"The most valuable aspect of the solution's the cost and human labor savings."

"It has improved self-service and customer satisfaction."

Cons

"Improvements in text extraction accuracy and pricing adjustments would be helpful."

"Customizations are very difficult, and they take time."

"One thing that I found is that Azure ML does not directly provide you with features on Google Cloud AI Platform, whereas Vertex provides some features of the platform."

"At first, there were only the user-managed rules to identify the best attributes of the individual. Then, we came up with a truth set and developed different machine learning models with the help of that truth set, so now it's completely machine learning."

"The technical support from Google is not very fast. I think it is about a five out of ten even though they have courses online where I can learn a lot, if I really need support, I have to wait a very long time."

"The initial setup was straightforward for me but could be difficult for others."

"I think it's the it it also has has evolved quite a bit over the last few years, and Google Cloud folks have been getting, more and more services. But I think from a improvement standpoint, so maybe they can look at adding more algorithms, so adding more AI algorithms to their suite."

"It could be more clear, and sometimes there are errors that I don't quite understand."

More Google Cloud AI Platform cons

"Honestly, I haven't seen any comparative report that has run the same data through two different artificial intelligence or machine learning capabilities to get something out of it. I would love to see that."

"If I consider how we want to use it in our organization, certain areas of improvement can be addressed. For instance, we want to use it with Generative AI, not like ChatGPT, but in a way intended for industrial use."

"Sometimes training the model is difficult."

"Scaling is limited in some use cases. They need to make it easier to expand in all aspects."

"In future releases, I would like to see a more flexible environment."

"The supporting language is limited."

"They should add more GPU processing power to improve performance, especially when dealing with large amounts of data."

Pricing and Cost Advice

"The licenses are cheap."

"The pricing is on the expensive side."

"The solution has an attractive starting program, which costs only 300 USD for a duration of three months. During this period, one can accomplish a lot of work on the solution."

"For every thousand uses, it is about four and a half euros."

"The price of the solution is competitive."

"I've only been using the free tier, but it's quite competitive on a service basis."

"The pricing model is good."

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837,501 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Computer Software Company

15%

Manufacturing Company

11%

Financial Services Firm

10%

University

Computer Software Company

16%

Educational Organization

11%

University

11%

Financial Services Firm

11%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about Google Cloud AI Platform?

A range of a a wide range of algorithms, EIM voice mails, which can be plugged in right away into your solution into into into our solution, and then have platform that provides know, to to come up...

What is your experience regarding pricing and costs for Google Cloud AI Platform?

For the most part, the pricing is perfect sinceit grows with the use of my app. In some cases, they could be more specific about the pricing, especially for some AI features.

What is your primary use case for Google Cloud AI Platform?

I use Google Cloud AI Platform due to Firebase and the many APIs that are available with it.

What do you like most about IBM Watson Machine Learning?

I was particularly interested in trying the AutoML feature to see how it handles data and proposes new models. The variety of models it provides is impressive.

What is your experience regarding pricing and costs for IBM Watson Machine Learning?

The solution is expensive.

What needs improvement with IBM Watson Machine Learning?

Sometimes training the model is difficult. We need to have at least a few different components to evaluate and understand the behavior of different users to have a very, very high accuracy in the m...

Azure OpenAI vs Google Cloud AI Platform

Comparisons

Compared 26% of the time

Hugging Face vs Google Cloud AI Platform

Compared 15% of the time

Microsoft Azure Machine Learning Studio vs Google Cloud AI Platform

Compared 14% of the time

Google Vertex AI vs Google Cloud AI Platform

Compared 8% of the time

Amazon SageMaker vs Google Cloud AI Platform

Compared 4% of the time

More Google Cloud AI Platform Competitors

Azure OpenAI vs IBM Watson Machine Learning

Compared 13% of the time

TensorFlow vs IBM Watson Machine Learning

Compared 9% of the time

IBM Watson Studio vs IBM Watson Machine Learning

Compared 4% of the time

Google Vertex AI vs IBM Watson Machine Learning

Compared 4% of the time

More IBM Watson Machine Learning Competitors

Product Reports

AI Development Platforms

Download Google Cloud AI Platform product report

AI Development Platforms

Download IBM Watson Machine Learning product report

Overview

Google AI Platform is a managed service that enables you to easily build machine learning models, that work on any type of data, of any size. Create your model with the powerful TensorFlow framework that powers many Google products, from Google Photos to Google Cloud Speech.

Google

IBM Watson Machine Learning helps data scientists and developers accelerate AI and machine-learning deployment. With its open, extensible model operation, Watson Machine Learning helps businesses simplify and harness AI at scale across any cloud.

IBM

Sample Customers

Carousell

Information Not Available

Google Cloud AI Platform vs. IBM Watson Machine Learning