Amazon Q vs Google Gemini AI comparison

Amazon Web Services (AWS) and Google are both solutions in the AI Code Assistants category. Amazon Web Services (AWS) is ranked #1 with an average rating of 8.3, while Google is ranked #3 with an average rating of 7.9. Amazon Web Services (AWS) holds a 7.9% mindshare in AICA, compared to Google’s 6.9% mindshare. Additionally, 100% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 86% of Google users who would recommend it.

Amazon Q

Read 20 Amazon Q reviews

1,766 Views
1,766 Comparison Views

100% willing to recommend

Google Gemini AI

Read 16 Google Gemini AI reviews

4,388 Views
1,448 Comparison Views

86% willing to recommend

Amazon Q

Google Gemini AI

Comparison Buyer's Guide

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Executive SummaryUpdated on Nov 9, 2025

Google Gemini AI and Amazon Q compete in the AI tools category. Google Gemini appears to have the upper hand in areas like data processing and seamless integration with Google Workspace, while Amazon Q excels in AWS platform integration and programming support.

Features: Google Gemini AI features multi-modal functionality, enabling text writing for social media, image generation, and managing large PDF files. Its integration with Google Workspace facilitates smooth access to internal documents, enhancing workflow efficiency. It is also proficient in processing large datasets and engaging in real-time interactions. Amazon Q is known for context-aware responses and seamless AWS integrations, providing productivity boosts through intelligent code suggestions and extensive documentation features. It's particularly suited for development projects, offering functionalities that improve code management and automate extensive changes.

Room for Improvement: Google Gemini AI could enhance customization options, accuracy of responses, and export functionalities. Further development in model justification and reducing hallucinations would be beneficial, alongside improvements in user engagement and creative capabilities. Amazon Q could benefit from better integration with IDEs, enhanced login session management, and support for image processing. Users would appreciate superior performance in complex scenarios and more integration options beyond AWS services, as well as improved speech analytics and real-time AI summaries.

Ease of Deployment and Customer Service: Google Gemini AI operates mainly in a public cloud, ensuring easy deployment, while Amazon Q offers both public and hybrid cloud options, catering to diverse organizational needs. Google's customer service is mixed, with potential delays, whereas Amazon is perceived as more reliable and comprehensive, despite facing occasional challenges with support and fees.

Pricing and ROI: Google Gemini AI provides competitive pricing with good value for initial trials, though costs may escalate as more features are added. The free model is accessible, but scaling can be expensive. In comparison, Amazon Q is seen as costly upfront, yet it offers value through AWS integration, although cost remains a concern, particularly for small enterprises and students who find it less affordable compared to competitors like ChatGPT.

To learn more, read our detailed Amazon Q vs. Google Gemini AI Report (Updated: December 2025).

Buyer's Guide

Amazon Q vs. Google Gemini AI

December 2025

Download the complete report

Helped 881,082 peers since 2012

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

3.9

Google Gemini AI improves productivity and efficiency but can incur costs, with variable financial impacts and competitive market standing.

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.

Uday Boya

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.

Ratndeep Kaushal

Assoicate Consultant at ZS

For more quotes and insights, download the Amazon Q report

For some of the models it's actually free. It doesn't cost anything, but once you get to production scenarios in which you have to use the API, you have to pay.

Luís Silva

Chief Technical Lead at a consultancy with 201-500 employees

For more quotes and insights, download the Google Gemini AI report

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

4.0

Customers have mixed feelings about Google Gemini AI support, appreciating online resources but noting potential accessibility issues.

Anytime you have an issue, you reach out to them, and they are willing to understand the issue you're facing.

Cyril Baah

Site reliability engineer at a tech services company with 201-500 employees

All queries were resolved promptly, and questions about capabilities were answered clearly.

Kaushiki Choubey

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.

Uday Boya

Ai Research Enthusiast And Developer at ADP

For more quotes and insights, download the Amazon Q report

They rely on a self-service approach, providing a lot of information online through blogs and documents.

Boris-Vishnevsky

CTO at AlphaNuTech

Microsoft has done better, though they're not great at it, but they seem to be more responsive.

Marcus Vandenbent

Senior Consultant at a outsourcing company with 201-500 employees

it's really difficult to reach them

Pranay Suyash

Chief Technology Officer at MedPiper Technologies Inc

For more quotes and insights, download the Google Gemini AI report

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

5.9

Google Gemini AI is praised for scalability but faces concerns over context size, costs, and computing power limitations.

For improvement, I suggest enhancing admin control or original level settings, utilizing analytics, and sharing prompt or response history.

Ayush Harsh

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.

Manoday Ahire

Cloud Architect at Acmegrade

Then we increased it with four types of data sources.

Jayesh Patil

Associate Software Engineer

For more quotes and insights, download the Amazon Q report

Google Gemini handles multiple PDF files and big files efficiently.

Moataz Ismail

Director at a tech services company with 501-1,000 employees

It can conduct research quickly, taking only five to seven minutes to produce a ten-page research document with a reasonable executive summary.

Boris-Vishnevsky

CTO at AlphaNuTech

If you want to grow the amount of information that you want to insert into the model before you provide an answer, you have to use different techniques.

Luís Silva

Chief Technical Lead at a consultancy with 201-500 employees

For more quotes and insights, download the Google Gemini AI report

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

7.1

Google Gemini AI is praised for its stable, reliable performance, with minor concerns about occasional hallucinations and alternatives.

The service is very stable.

Cyril Baah

Site reliability engineer at a tech services company with 201-500 employees

It maintains consistent performance, rarely crashing or lagging, even during prolonged use.

Ayush Harsh

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.

Manoday Ahire

Cloud Architect at Acmegrade

For more quotes and insights, download the Amazon Q report

Everything I've tried so far works without instability, bugs, or hallucinations.

Laurence Moseley

Emeritus Professor of Health Services Research at University of South Wales

Recently, Google Gemini has been very stable, without performance issues.

Moataz Ismail

Director at a tech services company with 501-1,000 employees

For more quotes and insights, download the Google Gemini AI report

Room For Improvement

Amazon Q needs improved IDE integration, longer sessions, better prompt handling, and enhanced multi-data reasoning for overall efficiency.

Google Gemini AI needs better customization, response speed, integration, code generation, and creative accuracy to improve user satisfaction.

The knowledge management integration, which is crucial in today's contact center business, should be more prominent in Amazon Connect.

Saurav Chakraborty

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.

Vaishnavi Rampure

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.

Uday Boya

Ai Research Enthusiast And Developer at ADP

For more quotes and insights, download the Amazon Q report

Google Gemini needs more accurate answers and the ability to export data to Excel or Google Sheets.

Moataz Ismail

Director at a tech services company with 501-1,000 employees

When working on a 20-page document, Google Gemini sometimes loses context about earlier parts.

Pranay Suyash

Chief Technology Officer at MedPiper Technologies Inc

Currently, it operates mostly autonomously, and while it provides structured activities, making the research configuration more accessible and flexible would be beneficial.

Boris-Vishnevsky

CTO at AlphaNuTech

For more quotes and insights, download the Google Gemini AI report

Setup Cost

Amazon Q's integration benefits AWS users with productivity gains, despite high pricing compared to ChatGPT's premium version.

Google Gemini AI pricing is competitive but can become costly with multiple licenses due to currency fluctuations.

The Pro plan seems to be a bit expensive.

Ratndeep Kaushal

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.

Uday Boya

Ai Research Enthusiast And Developer at ADP

For more quotes and insights, download the Amazon Q report

Google Gemini is free.

Laurence Moseley

Emeritus Professor of Health Services Research at University of South Wales

The per license cost is on par with others, but with the number of licenses, it becomes expensive.

Pranay Suyash

Chief Technology Officer at MedPiper Technologies Inc

The feature of Gemini 2.5 research is highly discounted.

Boris-Vishnevsky

CTO at AlphaNuTech

For more quotes and insights, download the Google Gemini AI report

Valuable Features

Amazon Q is praised for seamless AWS integration, efficient cloud management, robust security, and user-friendly real-time syncing.

Google Gemini AI enhances productivity with multi-modal features, automation, and seamless Google services integration for efficient task management.

Amazon Q helps boost productivity, enabling the delivery of quality and value to customers.

Cyril Baah

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.

Sri Durga U

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.

Satyaprakash Yadav

Software Developer at Enorvision AIML limited

For more quotes and insights, download the Amazon Q report

The most valuable feature of Google Gemini is its ability to function as an intelligent assistant, providing accurate answers to natural language queries and performing translations.

Laurence Moseley

Emeritus Professor of Health Services Research at University of South Wales

The AI capabilities of Google Gemini are a multi-modal LLM which allows me to pass documents, images, and texts in the same prompt.

Luís Silva

Chief Technical Lead at a consultancy with 201-500 employees

It provides an experimental search module capable of scanning hundreds of websites to deliver summarized data.

Moataz Ismail

Director at a tech services company with 501-1,000 employees

For more quotes and insights, download the Google Gemini AI report

Categories and Ranking

Amazon Q

Ranking in AI Code Assistants

1st

Average Rating

8.4

Reviews Sentiment

3.7

Number of Reviews

Ranking in other categories

No ranking in other categories

Google Gemini AI

Ranking in AI Code Assistants

3rd

Average Rating

7.8

Reviews Sentiment

6.0

Number of Reviews

Ranking in other categories

AI Writing Tools (1st), Large Language Models (LLMs) (1st), AI Proofreading Tools (1st)

Mindshare comparison

As of January 2026, in the AI Code Assistants category, the mindshare of Amazon Q is 7.9%, up from 2.8% compared to the previous year. The mindshare of Google Gemini AI is 6.9%, up from 4.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

AI Code Assistants Market Share Distribution
Product	Market Share (%)
Amazon Q	7.9%
Google Gemini AI	6.9%
Other	85.2%

AI Code Assistants

Featured Reviews

Uday Boya

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.

Read full review

Luís Silva

Chief Technical Lead at a consultancy with 201-500 employees

Tool proves competitive with cost-effectiveness and speed while benefiting decision-making and integration capabilities, but shows room for enhancing creativity and handling large data contextually

There is another benefit in that Google Gemini is highly competitive from a cost perspective. The cost per token is very competitive. It's not the best - the Chinese models such as DeepSeek are better, but I can't use them. From a cost perspective, between European and United States options, Google Gemini is very competitive. It's not only its cost, it's also very performing. The time it takes to process the prompts and context information is very fast. It's one of the fastest models in the market. That's another advantage. There are other models which are also very good in quality but not as fast, such as Anthropic Claude. Google Gemini currently has a very good balance. The AI capabilities of Google Gemini are a multi-modal LLM which allows me to pass documents, images, and texts in the same prompt. Being multi-modal makes my life easier. I don't have to translate information before I can work with it. Google provides free tools to test scenarios, which speeds up development and reduces costs. It's a very fast and accurate model with quality responses.

Read full review

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Top Industries

By visitors reading reviews

Computer Software Company

16%

Manufacturing Company

10%

Financial Services Firm

10%

Comms Service Provider

University

11%

Computer Software Company

Comms Service Provider

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	2
Midsize Enterprise	1
Large Enterprise	13

By reviewers
Company Size	Count
Small Business	6
Midsize Enterprise	6
Large Enterprise	6

Questions from the Community

What needs improvement with Amazon Q?

While using Amazon Q, I faced some challenges, such as navigating the interface initially.

See all answers

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 ...

See all answers

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...

See all answers

What is your experience regarding pricing and costs for Google Gemini?

The pricing of Google Gemini AI is not well understood, so no feedback can be provided on the cost. It was thought to have come together with the device subscription.

See all answers

What needs improvement with Google Gemini?

Google Gemini AI is not used much because it does not appear to be as responsive or as effective as Alexa when responding to questions, queries, instructions, or commands. When in a room with Googl...

See all answers

What is your primary use case for Google Gemini?

Google Gemini AI is used for common, basic digital assistant queries such as asking about the weather and the time. Often there are conflicting responses from Google Home, Google Home Mini, and the...

See all answers

Comparisons

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Compared 49% of the time

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Compared 18% of the time

GitHub CoPilot vs Amazon Q

Compared 13% of the time

Claude for Enterprise vs Amazon Q

Compared 7% of the time

ChatGPT Team - Enterprise vs Amazon Q

Compared 4% of the time

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Cursor vs Google Gemini AI

Compared 28% of the time

Grammarly Pro - Enterprise vs Google Gemini AI

Compared 17% of the time

Jasper vs Google Gemini AI

Compared 5% of the time

QuillBot vs Google Gemini AI

Compared 4% of the time

Windsurf vs Google Gemini AI

Compared 2% of the time

More Google Gemini AI Competitors

Product Reports

Buyer's Guide

Amazon Q

January 2026

Download Amazon Q product report

Buyer's Guide

Google Gemini AI

January 2026

Download Google Gemini AI product report

Also Known As

No data available

Google Bard

Overview

Amazon Q provides context-aware responses and integrates seamlessly with AWS, supporting efficient cloud task management, multi-language frameworks, and documentation capabilities. It's an asset for diverse development needs with auto-logging, intuitive interfaces, and fast deployment.

Amazon Q offers advanced natural language interpretation, enriching productivity with robust features like Git-related insights for tracking code changes and built-in redundancy. It supports multi-language frameworks and fosters efficient cloud operations via AWS integration. Despite reported feedback delays, challenging task handling, and limited customization, it remains valuable for enhancing productivity through code generation, data analysis, API integration, and AI model development. However, users desire more precise data handling, robust IDE integration, improved session management, and reduced CPU usage.

What are the key features of Amazon Q?

Context-Aware Responses: Delivers natural language understanding for meaningful interactions.
AWS Integration: Enables seamless management of cloud tasks with deep AWS connectivity.
Multi-Language Support: Accommodates diverse frameworks for global application.
Robust Documentation: Facilitates detailed code change insights and documentation capabilities.
Auto-Logging: Ensures accurate tracking of inaccuracies for continuous improvement.

What benefits and ROI should users expect?

Boosted Productivity: Enhances workflow through efficient task automation and intuitive design.
Seamless Cloud Operations: Streamlines cloud management via AWS integration.
Advanced Coding Assistance: Supports complex coding tasks and improves code quality.
Improved Accuracy: Reduces errors with auto-logging and context-aware processing.

In industries like education, Amazon Q enhances coding assistance and provides document search capabilities. It's utilized for business applications, including document processing, managing contact centers, and creating data visualization dashboards. Teams also leverage its potential in areas like API integration and automating deployment tasks.

Amazon Web Services (AWS)

Google Gemini AI integrates into Google Workspace for productivity, leveraging multi-modal capabilities to optimize tasks in text, image, and data handling. It balances cost and performance, enhancing operations through seamless real-time data processing and intelligent assistance.

Google Gemini AI is designed to enhance productivity through its integration with Google services, providing smart solutions for text writing, automated workflows, and image generation. It supports efficient data handling and intelligent searches, with real-time processing ensuring fast and accurate results. While it merges seamlessly with Google's offerings, there are areas for improvement like customization, data export functionality, and the interpretability of answers. Users have called for expanded context size, improved context retention, and enhanced factual accuracy along with creativity enhancements without hallucinations. Video creation features and a streamlined setup process are also on user wishlists.

What are the key features of Google Gemini AI?

Multi-modal Capabilities: Efficiently processes text, images, and data for enhanced task handling.
Google Workspace Integration: Seamless collaboration to boost productivity.
Real-time Data Processing: Ensures fast and accurate analyses and responses.
Intelligent Assistance: Facilitates dynamic searches and task automation.
Automated Workflows: Streamlines processes, saving time for users.

What benefits should users look for in reviews?

Cost and Performance: Achieves a balance for efficient operations.
Enhancement of Productivity: Boosts efficiency with seamless integration and task assistance.
Accurate Data Handling: Ensures precise data processing and real-time analysis.
Enhanced Creativity: Supports innovative solutions without hallucinations.

In specific industries, Google Gemini AI is employed to analyze financial services, enhance marketing strategies, conduct market research, manage internal documents, and provide real-time data analysis. It aids in creating test cases, generating emails, organizing documents, and enhancing intelligent searches, supporting strategic research initiatives efficiently.

Google

Buyer's Guide

Amazon Q vs. Google Gemini AI

December 2025

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