GitHub Copilot is presented as an AI pair programmer, that plugs into the user's editor. It then turns natural language prompts into code, offers multi-line function suggestions, speeds up test generation, filters out common vulnerable coding patterns, and blocks suggestions matching public code.
$10
per month
Google Gemini
Score 7.3 out of 10
N/A
Google Gemini (formerly Bard) is an AI assistant, presented as a creative and helpful collaborator. Gemini for Workspace is available via two plans: a Gemini Enterprise add-on, and a Gemini Business add-on.
N/A
Pricing
GitHub Copilot
Google Gemini
Editions & Modules
CoPilot for Individuals
$10
per month
CoPilot for Business
$19
per month per user
No answers on this topic
Offerings
Pricing Offerings
GitHub Copilot
Google Gemini
Free Trial
Yes
No
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
GitHub Copilot
Google Gemini
Considered Both Products
GitHub Copilot
Verified User
Anonymous
Chose GitHub Copilot
In terms of AI and developing tasks, GitHub Copilot is the only tool I have used so far. Copilot Work, Copilot Web, Copilot Teams, Copilot Excel, Copilot Word, Copilot Outlook, Copilot Power Point are other agents of Copilot that I use daily, but are all complementary of GitHub …
ChatGPT, Perplexity, and Grok are AI tools that developers use to boost productivity. However, GitHub Copilot outperforms them due to its tight integration with Visual Studio. GitHub Copilot can analyze all the code in your workspace and provide contextual assistance within …
It has historically worked much better. However, as all of this is relatively new technology it is hard to really judge something since most of the time you are kind of using a beta version of a product. I believe things will get better over time. That said, Microsoft copilot …
It is useful that copilot integrates so well with vscode, which is a very common IDE. I used tabnine for a little while but it was not that intuitive, and did not seem as helpful as github copilot was. I have enjoyed github copilot a lot, especially the ease of hitting the tab …
I have also used Anthropic's Claude code Its amazing, and I would say it is even better than GitHub Copilot. However, the only issue with claude code is its subscription price, which is very very high as compared to GitHub Copilot.
I used cursor AI as well, along with CoPilot. Curson has its own AI editor, but Copilot works with almost every code editor. So I don't need to depend on just one editor, and I get the flexibility to choose my own editors. The billing is also good and doesn't require many …
I like the fact that Gemini gives you 3 options of possible answers, and if they don't fit your needs, you are able to have other 3, until you get the best result. I have seen that the results that Gemini provides are more accurate than others. It also evolving frequently and …
Gemini seems very simple to use, veyr similar to ChatGPT, I wish they did have a capability such as ChatGPT projects one, so one can separate topics easily, it's very customizable, where I believe it defeats the others is that, is already very simple to use all of Google …
Google Gemini, when compared to other AI Tools, can be rated as follows. - Creativity: Best - Product Research: Best - User Interface: Best - Features: Very Good - Code Generation: Very Good - Documentation: Very Good - Accuracy: Good - Speed: Good Considering the above …
Google is free and included in my workspace subscription. Claude has no image generation. Google Gemini is also a Google product, so I assume it will be able to have a better understanding of the areas on Google I am trying to market. Overall, I think it's better than Claude, …
Hootsuite's OwlyGPT is great for social listening data, but Gemini is far ahead in terms of caption writing and other writing needs. Even for content creation ideas, I'd rather take the social listening insights then feed that to Gemini.
Gemini can fix its hallucination and generic output problem to get at part with Perplexity. Additionally, to beat in web search, it can produce citation after every information given. By this it can gain users trust. Sometimes, it doesn't give output only. such instances can be …
Google Gemini has the best context window in the market, the parameters are incredible and the speed is fantastic. It will lose for ChatGPT by seniority. It has the same tools now and the integration with the Google environment makes adding AI to any project, seamless. It is …
I like the UI of Google Gemini way more, and I also love the inbuilt integrations it has with open google docs and sheets. ChatGPT does not have (AFAIK) a Deep research section. Google Gemini Gems is also an awesome addition which helps to automate mundane/repetitive tasks. I …
Best at productivity based tasks that I encounter in the workplace. I spend about 20% of my time developing, and a majority of it doing overhead or operational tasks. Google Gemini is the best for analyzing spreadsheets, performing forecasting tasks, etc. If I was more …
Google Gemini stands tall in this league of AI chat tools. It has a good clean interface and good ability to answer questions quickly on questions related to research and development. However, It lacks integration with IDE tools such as Chat GPT's integration with Microsoft …
Google Gemini does pretty well against ChatGPT in regards to the information sourced and accuracy. Gemini's user interface is about the same, however I find it a bit cleaner, especially the way information is outputted. We use a lot of the Google Suite products, so access to …
Google Gemini has the advantage of being integrated with the Google family of products, very well know and used world abroad. Like, using workspace, Gemini can read my email and make a daily summary, search for urgent and important stuff, etc. Also, Gemini allows me to do …
Copilit is fantastic at the following: 1. Solving simple, well-defined problems, such as implementing an algorithm, manipulating a data structure, or string manipulation and regex. 2. Implementing simple APIs that are mainly CRUD in nature, with moderate business logic inside them, which may involve some processing or passing the data through an algorithm. 3. Implementation of well-defined activities, such as implementing a connection to an Oracle DB using Hibernate or JDBC, or implementing boilerplate code for a backend service to listen to Kafka events. It is not that great when it comes to understanding and implementing code in a proprietary DSL. It struggles when implementing a major feature across a complex codebase. I believe developers should also adopt the trust-but-verify paradigm when expecting highly secure or regulated code from GitHub Copilot.
Google Gemini AI features a Deep Research feature that helped us conduct thorough product research. We wanted to minimize the costs incurred by using SSL certificates in our organization, but we lacked knowledge on the subject. Google Gemini Deep Research did a thorough analysis and suggested ways to cut costs by switching vendors and using DV-type and/or wildcard SSL certificates. We also use Google Gemini for assistance during software development. However, Google Gemini seems to have limitations when suggesting code snippets for the Microsoft ecosystem.
Deep research for getting first business research draft from Gemini, post which i use series of prompts to improve it and use my understanding to refine it further
Canvas to produce structured business topic research and newsletter. Direct edits to the sections and making client ready reports
Learning mode to get help on step by step automation of AI workflows
Currently the document database caps out at 10, requiring us to condense some of our policies
It's large context window is a blessing and a curse. Sometimes it stops generating half way through a very ambitious request as it delivers page after page of content
There is no way to share Gems currently, so we have to publish guides to our employees on how to best configure them
I feel that GitHub Copilot's overall usability is good due to its tight integration with Visual Studio and the workspace. However, developers expect greater ease of use, as there is a learning curve to realize productivity gains with the tool fully. I think there is room for improvement in GitHub Copilot's UI integration within Visual Studio.
It is simple, has the same standard industry format, all the tools are accessible and recognizable. Whenever we are in the browser we can switch from one request to another while the first is still running. Little hallucination and the context window has no competitor on the market right now. The pricing is also the biggest advantage.
I used Cursor AI as well, along with CoPilot. Curson has its own AI editor, but Copilot works with almost every code editor. So I don't need to depend on just one editor, and I get the flexibility to choose my own editors. The billing is also good and doesn't require many coupons to write prompts.
Gemini seems very simple to use, veyr similar to ChatGPT, I wish they did have a capability such as ChatGPT projects one, so one can separate topics easily, it's very customizable, where I believe it defeats the others is that, is already very simple to use all of Google ecosystem, such as Drive, docs, sheets and else
