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Amazon Q vs Cursor comparison

 

Comparison Buyer's Guide

Executive Summary

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

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
Cursor
Ranking in AI Code Assistants
6th
Average Rating
9.0
Reviews Sentiment
6.5
Number of Reviews
1
Ranking in other categories
AI Software Development (6th)
 

Mindshare comparison

As of March 2026, in the AI Code Assistants category, the mindshare of Amazon Q is 7.5%, up from 4.9% compared to the previous year. The mindshare of Cursor is 23.4%, down from 31.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.
AI Code Assistants Mindshare Distribution
ProductMindshare (%)
Amazon Q7.5%
Cursor23.4%
Other69.1%
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.
Rusira Sathnindu - PeerSpot reviewer
Automation Engineer at a tech services company with 1-10 employees
AI coding has accelerated our feature delivery and has transformed how our team builds services
I have been noticing recently that Cursor introduced their own model, which is pretty limited; it is very fast, but it is not smart. They might have to improve that, along with the agent selection methodology. When you select auto, you expect it to use the best agent possible and think of the money savings, but it does not always work as expected, sometimes providing bad code or code that has bugs. I think the auto mode selection can improve. Another concern is the pricing; we have been paying a lot for Cursor recently, which I feel has increased within the last few months, possibly due to our usage going up. We are paying an amount similar to a developer's salary for Cursor now. I believe all the needed improvements are primarily around the auto agent selection mode and pricing. If they could be more transparent about it, that would be appreciated. We only see the bill at the end of the month, and it is often a high amount, so transparency in the pricing would be very helpful for us as developers.

Quotes from Members

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

Pros

"What I find best about Amazon Q is that I have used multiple AI tools such as Copilot and earlier Chat GPT, and I think that, apart from the other tools, Amazon Q has an edge because if I want to run any command, such as scanning my whole database and checking schemas, it can generate the command and ask for permission whether I want to execute it."
"Once the configuration is complete, users can manage all Kubernetes clusters using Amazon Q prompt, and when checking pods in the Kubernetes cluster, there is no need to use commands as users can simply write a prompt like 'Please show me the Kubernetes pods and namespace and all,' and Amazon Q automatically provides all the required details."
"The benefits of Amazon Q are that you don't need to build any code base at the backend to develop your RAG system or AI LLM-based summarization systems to do question-answer sets on the documents."
"What I find best about Amazon Q is that I have used multiple AI tools such as Copilot and earlier Chat GPT, and I think that, apart from the other tools, Amazon Q has an edge because if I want to run any command, such as scanning my whole database and checking schemas, it can generate the command and ask for permission whether I want to execute it."
"Amazon Q significantly reduced the time we spent on testing; it served as a great tool where we could ask questions, get answers, and complete testing efficiently."
"There is a lot of return on investment from using Amazon Q because the number of developers needed or the number of researchers needed, the number of automation people needed has been drastically reduced."
"Amazon Q understands natural language queries effectively and interacts robustly with company-specific data, making it simple to fine-tune with company-specific instructions, sources, and knowledge base."
"The explanation and documentation capabilities are excellent."
"Previously, tasks that would take weeks or months can now be completed within days because of these AI tools."
 

Cons

"Sometimes feedback is needed immediately. It takes a bit of time because there is a workload."
"Even though we connected with the support team of AWS, they were not able to resolve our issue, so we were disappointed at that moment."
"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."
"While great for standard tasks, it sometimes struggles with more complex or multi-layered problems in large code bases."
"If I start with a prompt in one tab and then try to continue in another, it does not retain that context."
"If I start with a prompt in one tab and then try to continue in another, it does not retain that context."
"I discovered that the application logs me out automatically after some time, which becomes problematic as I then lose access to my chat history."
"The model is not able to give answers properly with the traffic it is facing, so it needs to be scaled more."
"Another concern is the pricing; we have been paying a lot for Cursor recently, which I feel has increased within the last few months, possibly due to our usage going up."
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Top Industries

By visitors reading reviews
Computer Software Company
14%
Financial Services Firm
12%
Manufacturing Company
10%
Comms Service Provider
6%
Comms Service Provider
12%
Computer Software Company
11%
University
8%
Financial Services Firm
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business1
Midsize Enterprise2
Large Enterprise13
No data available
 

Questions from the Community

What needs improvement with Amazon Q?
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 c...
What is your primary use case for Amazon Q?
My main use case for Amazon Q is that we have access to it in our company, and on a daily basis, we receive a lot of requirements from clients to build websites and probably do all the other work a...
What advice do you have for others considering Amazon Q?
My advice to others looking into using Amazon Q is very simple. Go and take a shot on Amazon Q and build cool applications. If someone has any existing project, go ahead and start analyzing the com...
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Comparisons

 

Overview

Find out what your peers are saying about Amazon Web Services (AWS), GitHub, Google and others in AI Code Assistants. Updated: March 2026.
884,797 professionals have used our research since 2012.