Try our new research platform with insights from 80,000+ expert users

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 March 2026, in the AI Development Platforms category, the mindshare of Google Cloud AI Platform is 3.3%, down from 4.5% compared to the previous year. The mindshare of TensorFlow is 5.3%, up from 3.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Development Platforms Mindshare Distribution
ProductMindshare (%)
TensorFlow5.3%
Google Cloud AI Platform3.3%
Other91.4%
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."
"The feedback left about these tools was really helpful and informative for us"
"The initial setup is very straightforward."
"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."
"I have seen measurable benefits from Google Cloud AI Platform."
"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."
"The solution is able to read 90% of the documents correctly with a 10% error rate."
"Edge computing has some limited resources but TensorFlow has been improving in its features. It is a great tool for developers."
"TensorFlow improves my organization because our clients get a lot of investment from their investors and we are progressively improving the products. Every six months we release new features."
"What made TensorFlow so appealing to us is that you could run it on a cluster computer and on a mobile device."
"The most valuable feature of TensorFlow is deep learning. It is the best tool for deep learning in the market."
"The available documentation is extensive and helpful."
"The most valuable features are the frameworks and the functionality to work with different data, even when we have a certain quantity of data flowing."
"TensorFlow is easy to implement and offers inbuilt functions for various tasks."
"TensorFlow provides Insights into both data and machine learning strategies."
 

Cons

"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."
"The model management on Google Cloud AI Platform could be better."
"Improvements in text extraction accuracy and pricing adjustments would be helpful."
"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 solution can be improved by simplifying the process to make your own models."
"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."
"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."
"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."
"Personally, I find it to be a bit too much AI-oriented."
"It would be nice to have more pre-trained models that we can utilize within layers. I utilize a Mac, and I am unable to utilize AMD GPUs. That's something that I would definitely be like to be able to access within TensorFlow since most of it is with CUDA ML. This only matters for local machines because, in Azure, you can just access any GPU you want from the cloud. It doesn't really matter, but the clients that I work with don't have cloud accounts, or they don't want to utilize that or spend the money. They all see it as too expensive and want to know what they can do on their local machines."
"TensorFlow Lite only outputs to C."
"It would be cool if TensorFlow could make it easier for companies like us to program for running it across different hyperscalers."
"However, if I want to change just one thing in the implementation of TensorFlow functions I have to copy everything that they wrote and I change it manually if indeed it can be amended. This is really hard as it's written in C++ and has a lot of complications."
 

Pricing and Cost Advice

"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 pricing is on the expensive side."
"The price of the solution is competitive."
"The licenses are cheap."
"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."
"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."
"I did not require a license for this solution. It a free open-source solution."
"We are using the free version."
"TensorFlow is free."
"The solution is free."
report
Use our free recommendation engine to learn which AI Development Platforms solutions are best for your needs.
884,873 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Computer Software Company
12%
Manufacturing Company
11%
Financial Services Firm
10%
University
8%
Manufacturing Company
15%
Comms Service Provider
10%
University
9%
Financial Services Firm
9%
 

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 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 advice do you have for others considering Google Cloud AI Platform?
I have knowledge of it, and I do recommend Google Cloud AI Platform to other people. I would definitely rate the overall solution as an eight out of ten.
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: March 2026.
884,873 professionals have used our research since 2012.