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Amazon Q vs ChatGPT Team - Enterprise comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Nov 9, 2025

Review summaries and opinions

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

ROI

Sentiment score
1.7
Amazon Q enhances efficiency by saving time, reducing labor needs, and increasing deployment speed, though ROI wasn't universally measured.
Sentiment score
5.3
ChatGPT Team boosts ROI by 50% with faster task completion, reduced staffing needs, and justified investment costs through savings.
Overall, there is a lot of increase in the movement of moving things to production grade and building things that are production grade from earlier, and the number of people that are required to build that scale of applications has been drastically reduced.
AI Research Enthusiast and Developer at ADP
This indicates that if we use it in the organization, we would be able to save money for the client and potentially require fewer employees.
Assoicate Consultant at ZS
It has made the company more productive, generated more revenue, and as a whole, everything has improved.
Head of Marketing at a tech company with 51-200 employees
Overall, the platform has provided measurable efficiency and productivity gains, making the subscription cost more than justified by the time and resource savings.
Business Analyst at a tech vendor with 10,001+ employees
Overall, ChatGPT Team - Enterprise is cost effective and brings a return on investment for my use.
Business automation Expert at INSTRUTECH LIMITED
 

Customer Service

Sentiment score
2.0
Amazon Q's customer service is generally effective, with professionalism and expertise but some integration and communication challenges persist.
Sentiment score
6.1
ChatGPT Team - Enterprise is praised for timely support, professionalism, and excellent resources, though many rely on documentation.
Anytime you have an issue, you reach out to them, and they are willing to understand the issue you're facing.
Site reliability engineer at a tech services company with 201-500 employees
All queries were resolved promptly, and questions about capabilities were answered clearly.
Engineering Lead at Lloyds Banking Group PLC
The customer support for Amazon Q is fantastic because the moment I encounter some issues in Amazon Q, I reach out to them and they help me in figuring it out, and they help me in rapidly closing that issue.
AI Research Enthusiast and Developer at ADP
I would rate the available documentation as a 10.
Director Metropolitano de Gobierno Digital at a government with 10,001+ employees
When I inquired about documentation regarding costs and setup, they promptly responded within a few hours.
Website Developer And CMO at DishIs Technologies
Online resources are vast for optimizing results.
Senior Investment Analyst at a financial services firm with 1-10 employees
 

Scalability Issues

Sentiment score
3.3
Amazon Q excels in scalability, integrates with AWS, but requires improved traffic handling; users appreciate efficiency and reduced overhead.
Sentiment score
4.7
ChatGPT Team - Enterprise boasts superior scalability and flexibility, making it ideal for teams of varying sizes and needs.
For improvement, I suggest enhancing admin control or original level settings, utilizing analytics, and sharing prompt or response history.
Student at Sharda University
The model is not able to give answers properly with the traffic it is facing, so it needs to be scaled more.
Cloud Architect at Acmegrade
Then we increased it with four types of data sources.
Associate Software Engineer
ChatGPT Team - Enterprise is highly scalable for growing organizations, designed to support teams of various sizes, from small groups to hundreds or even thousands of users without a drop in performance or usability.
Business Analyst at a tech vendor with 10,001+ employees
It scales efficiently for mid-sized to large software teams.
Website Developer And CMO at DishIs Technologies
There is not over 50% speed up time overall with ChatGPT, but it definitely provides over 50% improvement for research-specific purposes.
Senior Investment Analyst at a financial services firm with 1-10 employees
 

Stability Issues

Sentiment score
4.2
Amazon Q is stable and reliable but can improve memory handling and offline performance; reliant on stable internet.
Sentiment score
5.6
The ChatGPT Team - Enterprise version offers high stability and reliability, with minimal downtime and prioritized uptime commitments.
The service is very stable.
Site reliability engineer at a tech services company with 201-500 employees
It maintains consistent performance, rarely crashing or lagging, even during prolonged use.
Student at Sharda University
The accuracy of that particular model provides high assurance that the result will be as the user wants it to be.
Cloud Architect at Acmegrade
Enterprise is stable. Most users report using it in real-world situations, handling routine workflows without regular disruptions or errors, and it is rated highly for stability and reliability in everyday enterprise contexts.
Business Analyst at a tech vendor with 10,001+ employees
Overall, ChatGPT Team - Enterprise's stability has been solid, and I have not observed any major outages or disruptions.
Website Developer And CMO at DishIs Technologies
 

Room For Improvement

Amazon Q needs improved IDE integration, longer sessions, better prompt handling, and enhanced multi-data reasoning for overall efficiency.
The enterprise requires enhanced accuracy, customization, multilingual capabilities, and ethical considerations for improved integration with internal systems.
The knowledge management integration, which is crucial in today's contact center business, should be more prominent in Amazon Connect.
Customer Success Manager at a tech vendor with 10,001+ employees
Out of 100%, Amazon Q will complete 80% and the remaining 20% of the errors, including build or runtime errors, you have to resolve manually.
Assistant consultant at Tata Consultancy
The moment I hit the context length of the window, it would ask me to clear the complete context, and it would lose the complete context of the chat that I had previously.
AI Research Enthusiast and Developer at ADP
You need the expertise to validate if what the prompt produces is correct.
Diretor at Hat Thinking
Teams now want no-code automations, including the ability to trigger summary generation after meetings, classification of support tickets, and scheduling of reports.
Product Analyst at a consultancy with 51-200 employees
For ultra-sensitive deployments, some organizations prefer tools that can run without cloud dependency, so having a secure on-premise or private cloud deployment option with the same collaboration compatibilities would be beneficial.
Business Analyst at a tech vendor with 10,001+ employees
 

Setup Cost

Amazon Q's integration benefits AWS users with productivity gains, despite high pricing compared to ChatGPT's premium version.
Enterprises upgraded to ChatGPT Team Enterprise for its cost-effectiveness and features, enhancing productivity and operational efficiency.
The Pro plan seems to be a bit expensive.
Assoicate Consultant at ZS
I was able to migrate the whole applications of my organization into Java 17, which is the latest version, in about ninety days.
AI Research Enthusiast and Developer at ADP
Without ChatGPT Team - Enterprise, I wouldn't have been able to do a tenth of what I do currently.
Head of Marketing at a tech company with 51-200 employees
The setup cost for ChatGPT was not very expensive.
Director Metropolitano de Gobierno Digital at a government with 10,001+ employees
 

Valuable Features

Amazon Q is praised for seamless AWS integration, efficient cloud management, robust security, and user-friendly real-time syncing.
ChatGPT Team - Enterprise boosts team efficiency with content creation, collaboration tools, integration ease, and customizable information processing.
Amazon Q helps boost productivity, enabling the delivery of quality and value to customers.
Site reliability engineer at a tech services company with 201-500 employees
The recent Agentic coding feature allows the tool to implement significant changes automatically, making it easier to maintain code by committing and pushing changes seamlessly while allowing for an easy undo option.
Senior Quality Engineer Data at Epsilon
The best feature of Amazon Q is that it has knowledge of my entire code base, entire repository, and its flows.
Software Developer at Enorvision AIML limited
I see a return on investment for ChatGPT because the time required results in significant savings.
Director Metropolitano de Gobierno Digital at a government with 10,001+ employees
With ChatGPT doing this, I save significant time because I can quickly get information about sources for subjects and main industry specialists regarding specific themes.
Diretor at Hat Thinking
We all have one of the most powerful tools ever at our disposal, so it's acted like a force multiplier.
Head of Marketing at a tech company with 51-200 employees
 

Categories and Ranking

Amazon Q
Ranking in AI Code Assistants
1st
Average Rating
8.4
Reviews Sentiment
3.7
Number of Reviews
20
Ranking in other categories
No ranking in other categories
ChatGPT Team - Enterprise
Ranking in AI Code Assistants
5th
Average Rating
8.6
Reviews Sentiment
5.3
Number of Reviews
15
Ranking in other categories
AI Writing Tools (2nd), Large Language Models (LLMs) (2nd), AI Proofreading Tools (2nd)
 

Mindshare comparison

As of February 2026, in the AI Code Assistants category, the mindshare of Amazon Q is 7.7%, up from 4.1% compared to the previous year. The mindshare of ChatGPT Team - Enterprise is 4.1%, up from 2.8% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Code Assistants Market Share Distribution
ProductMarket Share (%)
Amazon Q7.7%
ChatGPT Team - Enterprise4.1%
Other88.2%
AI Code Assistants
 

Featured Reviews

Uday Boya - PeerSpot reviewer
AI Research Enthusiast and Developer at ADP
Daily AI assistance has transformed debugging, automation, and rapid project delivery
One improvement for Amazon Q is that I use it in Visual Studio, and in Visual Studio, I am not given an option to upload an image in Amazon Q. Also, this is one part of it. The second part is the context window of Amazon Q is very less compared to other GenAI tools. The moment I would be in a deep research or deep development or deep debugging mode in Amazon Q, the moment I hit the context length of the window, it would ask me to clear the complete context, and it would lose the complete context of the chat that I had previously. The two major pain points are that I have Amazon Q in Visual Studio, but I am not given an option to upload an image as a reference in Amazon Q. The second part is the context window is so limited. The moment I deep dive into some discussion in terms of development or debugging or automation, I hit a context length of the window, and the moment I hit it, it would lose the complete context. It has an option of summarizing the complete context and having it as a memory, but it would not be sufficient because I would have given a lot of details in the chat by that time. I have mentioned the two points earlier, so those are the only two points that I have in mind for improvements needed for Amazon Q.
Vyas Shubham - PeerSpot reviewer
Product Analyst at a consultancy with 51-200 employees
Centralized knowledge has transformed collaboration and now streamlines documentation work
ChatGPT Team - Enterprise is already a very strong AI tool, but some improvements could enhance it further. Currently, context depends on what is provided, the prompts, and what is in memory. An improvement could be the automatic suggestion of relevant files or context based on queries. Cross-document semantic linking could be beneficial. Better handling of evolving knowledge would be useful, such as showing what changes have been made since last month. Additionally, teams want finer permissions such as read-only memory groups and scoped templates by role, departments, and temporary access tokens for contractors. I feel that more granular access controls are needed. Beyond APIs, teams now want no-code automations, including the ability to trigger summary generation after meetings, classification of support tickets, and scheduling of reports. Another improvement that comes to mind is the implementation of an in-app learning and training program. Built-in tutorials could help the team discover more advanced features and learn how to provide better prompts. The platform should provide best practices that show users what they need to do to get the best results. An in-app learning or training program would be valuable.
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Top Industries

By visitors reading reviews
Computer Software Company
15%
Manufacturing Company
10%
Financial Services Firm
10%
Comms Service Provider
6%
Computer Software Company
11%
Comms Service Provider
11%
Manufacturing Company
8%
University
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business2
Midsize Enterprise1
Large Enterprise13
By reviewers
Company SizeCount
Small Business7
Midsize Enterprise3
Large Enterprise6
 

Questions from the Community

What needs improvement with Amazon Q?
While using Amazon Q, I faced some challenges, such as navigating the interface initially.
What is your primary use case for Amazon Q?
I have completed a project where the company required testing R&D on Kubernetes. I tested it locally by installing MiniKube, Kubernetes, and all the containers. I configured the Kubernetes MCB ...
What advice do you have for others considering Amazon Q?
I find Amazon Q easy to use, and I believe anyone can use it without needing extensive technical knowledge. I would definitely recommend Amazon Q to other people; it's a great tool. I find it quite...
What needs improvement with ChatGPT?
ChatGPT Team - Enterprise is currently working well, and I do not see any need for improvements because it handles every project I run without complexity or delay. Everything on ChatGPT Team - Ente...
What is your primary use case for ChatGPT?
My main use case for ChatGPT Team - Enterprise is developing and coding, and for team collaboration, we have been using it for content marketing as well as coding. A specific example of how I use C...
What advice do you have for others considering ChatGPT?
I rate ChatGPT Team - Enterprise a ten out of ten because it is stable, flexible, and fully customizable. It also demonstrates the best functionality and performance so far. I advise others looking...
 

Also Known As

No data available
Rockset
 

Overview

 

Sample Customers

Information Not Available
1. Adobe 2. Cisco 3. Comcast 4. DoorDash 5. Expedia 6. Facebook 7. GitHub 8. IBM 9. Lyft 10. Microsoft 11. Netflix 12. Oracle 13. Pinterest 14. Reddit 15. Salesforce 16. Slack 17. Spotify 18. Square 19. Target 20. Twitter 21. Uber 22. Verizon 23. Visa 24. Walmart 25. Yelp 26. Zoom 27. Airbnb 28. Dropbox 29. eBay 30. Google 31. LinkedIn 32. Amazon
Find out what your peers are saying about Amazon Q vs. ChatGPT Team - Enterprise and other solutions. Updated: December 2025.
881,707 professionals have used our research since 2012.