Google Gemini vs. IBM watsonx Code Assistant Portfolio

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
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
IBM watsonx Code Assistant Portfolio
Score 8.9 out of 10
N/A
IBM watsonx™ Code Assistant for Red Hat® Ansible® Lightspeed demystifies the process of Ansible Playbook creation through generative AI-powered content recommendations. Purpose-built to accelerate IT Automation, the product is designed to deliver automation content recommendations for an enhanced Ansible experience.N/A
Pricing
Google GeminiIBM watsonx Code Assistant Portfolio
Editions & Modules
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Offerings
Pricing Offerings
Google GeminiIBM watsonx Code Assistant Portfolio
Free Trial
NoYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Best Alternatives
Google GeminiIBM watsonx Code Assistant Portfolio
Small Businesses

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Medium-sized Companies

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Enterprises
Oracle Digital Assistant
Oracle Digital Assistant
Score 7.9 out of 10

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User Ratings
Google GeminiIBM watsonx Code Assistant Portfolio
Likelihood to Recommend
8.0
(0 ratings)
8.2
(0 ratings)
Usability
8.2
(0 ratings)
-
(0 ratings)
User Testimonials
Google GeminiIBM watsonx Code Assistant Portfolio
Likelihood to Recommend
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.
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I would recommend for understanding your Mainframe components not for the GenAI piece involved from just my experience. The explanations were not up to the quality we wanted but its deterministic side provided a lot of value for different members of my team. The visuals would be great. I am not sure where it currently stands
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Pros
  • 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
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  • It can automatically revamp specific parts of the COBOL code and very useful when we want to maintain the existing codebase but improve its structure. I can highlight a block of COBOL code and use Watsonx Assistant to suggest ways to simplify and optimize it.
  • Legacy codes, mostly written in COBOL, are cryptic and difficult to understand. Watsonx Assistant analyzes the code and provides insights into its functionalities and dependencies. A great help when working on older applications where understanding the codebase is crucial.
  • A step-by-step approach to modernize our applications slowly and steadily, so that we can control the process better. I don't have to change everything at once. Instead, I can focus on specific COBOL modules and automatically convert them to Java.
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Cons
  • 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
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  • IDE integration is not always optimal
  • I wish it could it could generate the code of an entire WEB site based on user specifications
  • I with there was a functionality to generate code based on design documents such as Sequence Diagrams, Database Architecture etc.
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Usability
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.
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Alternatives Considered
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
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Security is very important in the mainframe world. At Watsonx, we work in the trusted Z environment, which has strong security rules, stricter than those of other cloud-based solutions. My domain is primarily mainframe modernization and Watsonx Code Assistant for Z is specifically used to understand and work with COBOL, the language used majorly in mainframe environments, not any general-purpose language that used in various platforms. It understands the nuances of COBOL and Assembler specific to the Z environment, something crucial for my work.
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Return on Investment
  • Free way to gain another team member
  • Helps me be more efficient and overcome blocks in my workflow
  • Speeds up my ability to update our website's calendar by easily double if not more
  • Allows me to dabble in areas that I have no expertise in such as coding
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  • While manual review and adjustments are still needed, it's a 50-70% reduction in manual coding. Think about it - a project estimated to take a year is done in 4-6 months.
  • We've been able to introduce new features and improvements more quickly by updating our technology faster. One relevant example is we recently released an important update to our main product 45 days earlier than planned.
  • It has been a smart move and it's really paid off for our company. We've cut down a lot of time we used to spend doing things manually. We now spend our resources more wisely, work faster and finish projects sooner and as a result, we've reduced our development costs by 25%.
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ScreenShots

IBM watsonx Code Assistant Portfolio Screenshots

Screenshot of Flexibility to deploy large language model either on-premises or as-a-service