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Google Cloud AI Platform vs TensorFlow 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 Cloud AI Platform
Ranking in AI Development Platforms
10th
Average Rating
7.8
Reviews Sentiment
7.1
Number of Reviews
9
Ranking in other categories
No ranking in other categories
TensorFlow
Ranking in AI Development Platforms
8th
Average Rating
8.8
Reviews Sentiment
7.4
Number of Reviews
19
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of December 2025, in the AI Development Platforms category, the mindshare of Google Cloud AI Platform is 3.3%, down from 5.4% compared to the previous year. The mindshare of TensorFlow is 6.4%, up from 4.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Market Share Distribution
ProductMarket Share (%)
TensorFlow6.4%
Google Cloud AI Platform3.3%
Other90.3%
AI Development Platforms
 

Featured Reviews

TJ
Owner at Go knowledge
Streamlines app development with dynamic databases and an easy setup
I used Oracle APEX before Google Cloud AI Platform. Oracle APEX is a free tool, except for the Oracle database, which I can only use with it. To have more freedom, I chose Firebase and Google's solutions as it allows me to run it on a hosted server if I want to.
TJ
Owner at Go knowledge
Has good stability, but the process of creating models could be more user-friendly
The platform integrates well with other tools, especially Python, which we use to create models. These models can be deployed on mobile devices, which perfectly suits our requirements. It supports our AI-driven initiatives very well by producing AI models, which is its primary function. I recommend it for those seeking specialized scripting. However, it's important to consider other options as well. It is better suited for specialists in the field and is less user-friendly than general tools like Excel. I rate it overall at six out of ten. While it is a powerful tool, other software options are slightly simpler for training models.

Quotes from Members

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

Pros

"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."
"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."
"Some of the valuable features are the vast amount of services that are available, such as load balancer, and the AI architecture."
"The platform's Google Vision API is particularly valuable."
"I have seen measurable benefits from Google Cloud AI Platform."
"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."
"The initial setup is very straightforward."
"The solution is able to read 90% of the documents correctly with a 10% error rate."
"I would rate the solution an eight out of ten. I am not a developer but more of an account manager. I can find what I want with TensorFlow. I haven’t contacted technical support for any issues. Since TensorFlow is vastly documented on the internet, I usually find some good websites where people exchange their views about the solution and apply that."
"TensorFlow is easy to implement and offers inbuilt functions for various tasks."
"Optimization is very good in TensorFlow. There are many opportunities to do hyper-parameter training."
"Google is behind TensorFlow, and they provide excellent documentation. It's very thorough and very helpful."
"What made TensorFlow so appealing to us is that you could run it on a cluster computer and on a mobile device."
"TensorFlow provides Insights into both data and machine learning strategies."
"TensorFlow is an efficient product for building neural networks."
"It is easy to use and learn."
 

Cons

"Customizations are very difficult, and they take time."
"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."
"It could be more clear, and sometimes there are errors that I don't quite understand."
"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."
"Improvements in text extraction accuracy and pricing adjustments would be helpful."
"The model management on Google Cloud AI Platform could be better."
"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."
"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."
"TensorFlow deep learning takes a lot of computation power. The more systems you can use, the easier it is. That's a good ability, if you can make a system run immediately at the same time on the same task, it's much faster rather than you having one system running which is slower. Running systems in parallel is a complex situation, but it can improve. There is a lot of work involved."
"In terms of improvement, we always look for ways they can optimize the model, accelerate the speed and the accuracy, and how can we optimize with our different techniques. There are various techniques available in TensorFlow. Maintaining accuracy is an area they should work on."
"I would love to have a user interface like a programming interface. You need to have a set of menus where you can put things together in a graphical interface. The complete automation of the integration of the modules would also be interesting. It’s more like plumbing as opposed to a fully automated environment."
"The process of creating models could be more user-friendly."
"The solution is hard to integrate with the GPUs."
"There are a lot of problems, such as integrating our custom code. In my experience model tuning has been a bit difficult to edit and tune the graph model for best performance. We have to go into the model but we do not have a model viewer for quick access."
"TensorFlow Lite only outputs to C."
"I know this is out of the scope of TensorFlow, however, every time I've sent a request, I had to renew the model into RAM and they didn't make that prediction or inference. This makes the point for the request that much longer. If they could provide anything to help in this part, it will be very great."
 

Pricing and Cost Advice

"The pricing is on the expensive side."
"The price of the solution is competitive."
"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 licenses are cheap."
"TensorFlow is free."
"It is open-source software. You don't have to pay all the big bucks like Azure and Databricks."
"I rate TensorFlow's pricing a five out of ten."
"The solution is free."
"I did not require a license for this solution. It a free open-source solution."
"We are using the free version."
"I think for learners to deploy a project, you can actually use TensorFlow for free. It's just amazing to have an open-source platform like TensorFlow to deploy your own project. Here in Russia no one really cares about licenses, as it is totally open source and free. My clients in the United States were also pleased to learn when they enquired, that licensing is free."
"I am using the open-source version of TensorFlow and it is free."
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Top Industries

By visitors reading reviews
Computer Software Company
14%
Financial Services Firm
10%
Manufacturing Company
10%
University
8%
Manufacturing Company
14%
Computer Software Company
11%
University
9%
Financial Services Firm
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business5
Midsize Enterprise2
Large Enterprise2
By reviewers
Company SizeCount
Small Business12
Midsize Enterprise3
Large Enterprise3
 

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 is your experience regarding pricing and costs for TensorFlow?
I am not familiar with the pricing setup cost and licensing.
What needs improvement with TensorFlow?
Providing more control by allowing users to build custom functions would make TensorFlow a better option. It currently offers inbuilt functions, however, having the ability to implement custom libr...
What is your primary use case for TensorFlow?
I've used TensorFlow for image classification tasks, object detection tasks, and OCR.
 

Overview

 

Sample Customers

Carousell
Airbnb, NVIDIA, Twitter, Google, Dropbox, Intel, SAP, eBay, Uber, Coca-Cola, Qualcomm
Find out what your peers are saying about Google Cloud AI Platform vs. TensorFlow and other solutions. Updated: December 2025.
879,259 professionals have used our research since 2012.