IBM Machine Learning for z/OS vs. IBM watsonx.ai

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM Machine Learning for z/OS
Score 10.0 out of 10
N/A
IBM Machine Learning for z/OS® brings AI to transactional applications on IBM zSystems. It can embed machine learning and deep learning models to deliver real-time insight, or inference every transaction with minimal impact to operational SLAs.N/A
IBM watsonx.ai
Score 8.7 out of 10
N/A
Watsonx.ai is part of the IBM watsonx platform that brings together new generative AI capabilities, powered by foundation models, and traditional machine learning into a studio spanning the AI lifecycle. Watsonx.ai can be used to train, validate, tune, and deploy generative AI, foundation models, and machine learning capabilities, and build AI applications with less time and data.
$0
Pricing
IBM Machine Learning for z/OSIBM watsonx.ai
Editions & Modules
No answers on this topic
Free Trial
$0
ML functionality (20 CUH limit /month); Inferencing (50,000 tokens / month)
Standard
$1,050
Monthly tier fee; additional usage based fees
Essentials
Contact Sales
Usage based fees
Offerings
Pricing Offerings
IBM Machine Learning for z/OSIBM watsonx.ai
Free Trial
NoYes
Free/Freemium Version
NoYes
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsPricing for watsonx.ai includes: model inference per 1000 tokens and ML tools and ML runtimes based on capacity unit hours.
More Pricing Information
Community Pulse
IBM Machine Learning for z/OSIBM watsonx.ai
Features
IBM Machine Learning for z/OSIBM watsonx.ai
AI Development
Comparison of AI Development features of Product A and Product B
IBM Machine Learning for z/OS
-
Ratings
IBM watsonx.ai
5.5
1 Ratings
1% above category average
Machine learning frameworks00 Ratings5.51 Ratings
Data management00 Ratings4.51 Ratings
Data monitoring and version control00 Ratings4.51 Ratings
Automated model training00 Ratings4.51 Ratings
Managed scaling00 Ratings6.41 Ratings
Model deployment00 Ratings6.41 Ratings
Security and compliance00 Ratings6.41 Ratings
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IBM Machine Learning for z/OSIBM watsonx.ai
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Medium-sized Companies
Posit
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Score 10.0 out of 10
InterSystems IRIS
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Score 7.8 out of 10
Enterprises
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Score 10.0 out of 10
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Score 8.2 out of 10
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User Ratings
IBM Machine Learning for z/OSIBM watsonx.ai
Likelihood to Recommend
10.0
(2 ratings)
9.1
(33 ratings)
Likelihood to Renew
-
(0 ratings)
6.4
(1 ratings)
Usability
-
(0 ratings)
7.8
(6 ratings)
Support Rating
4.0
(1 ratings)
-
(0 ratings)
Ease of integration
-
(0 ratings)
6.4
(2 ratings)
Product Scalability
-
(0 ratings)
9.1
(1 ratings)
User Testimonials
IBM Machine Learning for z/OSIBM watsonx.ai
Likelihood to Recommend
IBM
IBM Watson Machine Learning is an AI-based scalable self-learning model for any type of business. It can be used to help any company automate repetitive tasks, predict future trends, and make data-driven decisions. I used it to predict stock prices based on certain variables. It works well, cost me nothing, and gives me the ability to create my own AI-based models that I can use for any purpose.
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IBM
I have built a code accelerator tool for one of the IBM product implementation. Although there was a heavy lifting at the start to train the model on specifics of the packaged solution library and ways of working; the efficacy of the model is astounding. Having said that, watsonx.ai is very well suited for customer service automation, healthcare data analytics, financial fraud detection, and sentiment analysis kind of projects. The Watsonx.ai look and feel is little confusing but I understand over a period of time , it will improve dramatically as well. I do feel that Watsonx.ai has certain limitations from cross-platform deployment flexibility. If an organization is deeply invested in a multi-cloud environment, Watson's integration on other cloud platforms may not be seamless comported to other AI platforms.
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Pros
IBM
  • Good machine learning tool
  • Easy integration
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IBM
  • It allows specialists to apply several base models for specific subtasks in the field of NLP.
  • Gives the availability of many models developed for AI enhancement for different solutions.
  • Has incorporated functionality for data governance and security to support access to AI tools by multiple users.
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Cons
IBM
  • Proper usage of REST API documentation is missing.
  • Not localization friendly, cannot support regional or local language documents.
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IBM
  • IBM watsonx.ai is expensive than other platforms.
  • Limited integraions though it has many but still some tools integrations not there for medical usecase
  • Its little difficult to learn as right now not many open reseouces
  • Community is not that strong to get any answer
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Likelihood to Renew
IBM
No answers on this topic
IBM
I still don't have enough experience, but i have seen a lot of demos and i have made some real world scenarios and so far so long every thing looks fine. I was at IBM Think 2025 and IBM TechXchange 2025 and the labs were really usefull and simple to understand.
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Usability
IBM
No answers on this topic
IBM
I needed some time to understand the different parts of the web UI. It was slightly overwhelming in the beginning. However, after some time, it made sense, and I like the UI now. In terms of functionality, there are many useful features that make your life easy, like jumping to a section and giving me a deployment space to deploy my models easily.
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Support Rating
IBM
IBM had a hard time providing business level support. There were a lot of data scientists and technology experts but rarely a simple business person shows up. Also the way IBM operates IBM Consulting has competing priorities as compared to IBM Technology. This has resulted in a lot of confusion at the client's end.
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IBM
I still don't have enough experience, but i have seen a lot of demos and i have made some real world scenarios and so far so long every thing looks fine. I was at IBM Think 2025 and IBM TechXchange 2025 and the labs were really usefull and simple to understand.
Read full review
Alternatives Considered
IBM
We have been using Microsoft Azure as a machine learning tool. But the challenges remain the same. These are all tools that you need a robust analysis before a decision on the tool. Unfortunately, the technology company cannot make that determination due to lack of core business understanding. Without that the project is doomed.
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IBM
IBM watsonx.ai has been far superior to that of Chat GPT AI. the UI elements prompt responses and overall execution of the AI was much better and more accurate compared to the competition. I can not recommend using this platform enough. Great job IBM. I hope the team behind this project continues to grow and prosper.
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Scalability
IBM
No answers on this topic
IBM
I still don't have enough experience, but i have seen a lot of demos and i have made some real world scenarios and so far so long every thing looks fine. I was at IBM Think 2025 and IBM TechXchange 2025 and the labs were really usefull and simple to understand.
Read full review
Return on Investment
IBM
  • Create secure business environment.
  • Save upto 90% of manual labor.
  • Improve my sales and marketing ROI.
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IBM
  • Time saving to set up the infrastructure - without watsonx.ai we would have had to set up everything individually
  • The first point translates directly into cost savings
  • The compliance aspect was a game changer for us and provided us with the confidence to focus all our efforts only on IBM watsonx.ai
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ScreenShots

IBM watsonx.ai Screenshots

Screenshot of the foundation models available in watsonx.ai. Clients have access to IBM selected open source models from Hugging Face, as well as other third-party models, and a family of IBM-developed foundation models of different sizes and architectures.Screenshot of the Prompt Lab in watsonx.ai, where AI builders can work with foundation models and build prompts using prompt engineering techniques in watsonx.ai to support a range of Natural Language Processing (NLP) type tasks.Screenshot of the Tuning Studio in watsonx.ai, where AI builders can tune foundation models with labeled data for better performance and accuracy.Screenshot of the data science toolkit in watsonx.ai where AI builders can build machine learning models automatically with model training, development, visual modeling, and synthetic data generation.