Azure OpenAI vs Google Cloud AI Platform comparison

Microsoft and Google are both solutions in the AI Development Platforms category. Microsoft is ranked #1 with an average rating of 7.9, while Google is ranked #8 with an average rating of 7.8. Microsoft holds a 12.9% mindshare in AIDP, compared to Google’s 4.3% mindshare. Additionally, 93% of Microsoft users are willing to recommend the solution, compared to 100% of Google users who would recommend it.

Azure OpenAI

Read 33 Azure OpenAI reviews

8,663 Views
7,905 Comparison Views

93% willing to recommend

Google Cloud AI Platform

Read 9 Google Cloud AI Platform reviews

3,212 Views
2,467 Comparison Views

100% willing to recommend

Azure OpenAI

Google Cloud AI Platform

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 4, 2024

Google Cloud AI Platform and Azure OpenAI are competitive in the AI and cloud services market. Azure OpenAI edges ahead due to its advanced natural language processing and AI models, while Google Cloud AI Platform is favored for its cost-effectiveness and streamlined customer support.

Features: Google Cloud AI Platform offers robust machine learning capabilities, smooth integration with Google Cloud services, and intuitive model training. Azure OpenAI, on the other hand, provides superior natural language processing, advanced AI models like ChatGPT, and excellent solutions for information retrieval and question-answering.

Room for Improvement: Google Cloud AI Platform could enhance its natural language processing capabilities and expand its advanced AI model offerings. Additionally, improvements in complex AI solution support would be beneficial. Azure OpenAI needs to simplify its deployment model, improve geographic availability, and manage rate limitations effectively.

Ease of Deployment and Customer Service: Google Cloud AI Platform ensures straightforward deployment with comprehensive customer support, making it easy to implement. Azure OpenAI offers a more complex deployment but provides specialized support tailored for AI implementations.

Pricing and ROI: Google Cloud AI Platform presents a flexible pricing model with predictable costs, attracting cost-conscious businesses. While Azure OpenAI's pricing can be higher, its cutting-edge AI capabilities justify the potential for a higher ROI by enhancing AI-driven growth through superior technology investments.

To learn more, read our detailed Azure OpenAI vs. Google Cloud AI Platform Report (Updated: March 2025).

Buyer's Guide

Azure OpenAI vs. Google Cloud AI Platform

March 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

Azure OpenAI

Ranking in AI Development Platforms

1st

Average Rating

7.8

Reviews Sentiment

6.7

Number of Reviews

Ranking in other categories

No ranking in other categories

Google Cloud AI Platform

Ranking in AI Development Platforms

8th

Average Rating

7.8

Reviews Sentiment

7.1

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2025, in the AI Development Platforms category, the mindshare of Azure OpenAI is 12.9%, down from 21.1% compared to the previous year. The mindshare of Google Cloud AI Platform is 4.3%, down from 6.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

AI Development Platforms

Featured Reviews

Viswanath Barenkala

Associate Vice President at State Street

Offers tools to moderate generated content and guidance to safely design applications, but it is not consistently accessible

Instead of a feature, the GPT-4 model has been most beneficial for automating tasks. We transitioned from GPT-3.5 to GPT-4 and actively use it. However, we face limitations due to geographic availability, subscription constraints, and rate limiting, which we are currently negotiating and working towards optimizing. While we haven't formally benchmarked Azure OpenAI's language understanding against industry standards, we find it performs well about 70-80% of the time. Occasionally, we need to refine our queries and adapt our systems accordingly to improve accuracy and effectiveness.

Read full review

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

Quotes from Members

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

Pros

"Two aspects I appreciate are the turnaround time and ease of use. As it's a managed service, the quick turnaround is beneficial, and the simple interface makes it easy to work with. Performance and scalability are also strong points since you can scale as needed."

"It's very powerful. It allows users to query our documents using natural language and receive answers in the same way. This makes our product information much more accessible than traditional keyword-based search."

"OpenAI integrates seamlessly with the broader Microsoft Azure ecosystem, and that provides synergies with the other solutions. This integration makes it much easier to build solutions."

"Azure OpenAI is very easy to use instead of AWS services."

"Generative AI or GenAI seems to be the best part of the solution."

"The high precision of information extraction is the most valuable feature."

"The most crucial aspect is the conversational capability, where you can simply ask questions, and it provides answers based on your content and documents, particularly tailored to your specific environment."

"Azure's integration with OpenAI's GPT is beneficial as well, especially for text generation tasks."

More Azure OpenAI 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 platform's Google Vision API is particularly valuable."

"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."

"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."

"I think the user interface is quite handy, and it is easy to use as compared to the other cloud platforms."

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

More Google Cloud AI Platform pros

Cons

"We encountered challenges related to question understanding."

"Since we don't train the model on our data, it's a struggle to ensure OpenAI answers questions exclusively from our data. During user testing, we found ways to make the system provide answers from outside sources."

"Sometimes, it gives answers in English, even when the request is in Polish."

"I noticed there are no instructional videos or guides on the network portal for initial configurations. There is limited information available, and this is a concern for me. I would like to see more resources and guides to address these issues."

"Azure OpenAI is not an optimized tool yet, making it one of its shortcomings where improvements are required."

"Deployment was slightly complex for me to understand."

"Azure could significantly benefit from including more LLM models apart from OpenAI, as I often need to switch clouds when a model doesn't meet my requirements."

"The UI could be a little easier."

More Azure OpenAI cons

"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 solution can be improved by simplifying the process to make your own models."

"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."

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

"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."

More Google Cloud AI Platform cons

Pricing and Cost Advice

"The cost structure depends on the volume of data processed and the computational resources required."

"Cost-wise, the product's price is a bit on the higher side."

"Regarding pricing and licensing, it's a bit complex due to the minimum purchase requirement for PTO units. We're evaluating the best approach between PTE and pay-as-you-go models. Our organization is cautious about committing to PTE due to the fixed bandwidth reservation, while pay-as-you-go doesn't offer enough flexibility. We're discussing these matters with legal teams to ensure compliance and data security."

"We started with monthly payments, but we plan to switch to yearly billing once we've stabilized our solution."

"If you consider the long-term aspect of any project, Azure OpenAI is a costly solution."

"The tool costs around 20 dollars a month."

"It's a token-based system, so you pay per token used by the model."

"I'm uncertain about the licensing, specifically the pricing. This falls under the purview of other teams, particularly the sales teams. I am not informed about the pricing details."

More Azure OpenAI 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 licenses are cheap."

"The price of the solution is competitive."

"The pricing is on the expensive side."

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845,040 professionals have used our research since 2012.

Top Industries

By visitors reading reviews

Financial Services Firm

15%

Computer Software Company

13%

Manufacturing Company

11%

Government

Computer Software Company

16%

Financial Services Firm

11%

Manufacturing Company

University

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

Questions from the Community

What do you like most about Azure OpenAI?

The product is easy to integrate with our IT workflow.

See all answers

What is your experience regarding pricing and costs for Azure OpenAI?

The pricing is very good for handling various kinds of jobs. While small jobs are manageable, more complex jobs require a higher model, which is a bit challenging.

See all answers

What needs improvement with Azure OpenAI?

Maybe with the next release, the response will be more precise and more human-like.

See all answers

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...

See all answers

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.

See all answers

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.

See all answers

Comparisons

Google Vertex AI vs Azure OpenAI

Compared 42% of the time

Hugging Face vs Azure OpenAI

Compared 13% of the time

Amazon SageMaker vs Azure OpenAI

Compared 12% of the time

Microsoft Azure Machine Learning Studio vs Azure OpenAI

Compared 8% of the time

IBM Watson Studio vs Azure OpenAI

Compared 3% of the time

More Azure OpenAI Competitors

IBM Watson Machine Learning vs Google Cloud AI Platform

Compared 28% 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 11% of the time

Google Vertex AI vs Google Cloud AI Platform

Compared 6% of the time

Amazon SageMaker vs Google Cloud AI Platform

Compared 3% of the time

More Google Cloud AI Platform Competitors

Product Reports

Buyer's Guide

Azure OpenAI

March 2025

Download Azure OpenAI product report

Buyer's Guide

AI Development Platforms

March 2025

Download Google Cloud AI Platform product report

Overview

Azure OpenAI integrates advanced language models with robust security for precise information extraction and task automation. Its seamless Azure integration and drag-and-drop interface simplify implementation and enhance accessibility.

Azure OpenAI offers a comprehensive suite of features designed for efficient data processing and task automation. It provides high precision in extracting information and strong conversational capabilities, crucial for developing chatbots and customer support systems. Its integration with Azure ensures seamless data handling and security, addressing key enterprise requirements. Users can employ its versatile GPT models for diverse applications such as predictive analytics, summarizing large documents, and competitive benchmarking. Despite its strengths, it faces challenges like latency, inadequate regional support, and limited integration of new technologies. Improvements in model fine-tuning and more flexible configuration are desired by users.

What features make Azure OpenAI a reliable choice?

High Precision: Ensures accurate data extraction suitable for critical applications.
Conversational Capabilities: Facilitates the creation of sophisticated chatbots.
Azure Integration: Seamlessly connects with Azure services for enhanced functionality.
Automation Support: Automates repetitive tasks, improving efficiency.
Security Features: Offers robust protection for sensitive data.
Drag-and-Drop Environment: Simplifies user interaction and deployment.

What benefits and ROI should users consider?

Natural Language Processing: Provides superior language model performance.
Quick Implementation: Reduces time to deploy applications.
Scalability: Supports growing business needs with ease.
Versatile GPT Models: Applicable across different industry workflows.

Azure OpenAI is implemented across industries like healthcare, finance, and education for tasks like invoice processing, digitalizing records, and language translation. It enhances policy management, document assimilation, and customer support with predictive analytics and keyword extraction. Organizations in such sectors benefit from streamlined workflows and task automation.

Microsoft

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

Sample Customers

Information Not Available

Carousell

Buyer's Guide

Azure OpenAI vs. Google Cloud AI Platform

March 2025

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