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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM watsonx.ai

    Score8.3 out of 10
    N/AWatsonx.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

    OpenAI API Platform

    Score9.6 out of 10
    N/AThe OpenAI API platform provides a simple interface to AI models for text generation, natural language processing, computer vision, and other purposes.

    $0

    per  1K tokens

    Pricing
    IBM watsonx.aiOpenAI API Platform
    Editions & Modules
    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
    Ada
    $0.0008
    per  1K tokens
    Babbage
    $0.0012
    per  1K tokens
    Curie
    $0.0060
    per  1K tokens
    Davinci
    $0.0600
    per  1K tokens
    Offerings
    Pricing Offerings
    IBM watsonx.aiOpenAI API Platform
    Free Trial
    YesNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    YesNo
    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 watsonx.aiOpenAI API Platform
    Considered Both Products
    IBM
    Chose IBM watsonx.ai
    To identify IBM watsonx.ai, our team has reviewed other AI choices we met from Google's Vertex AI and AI services provided by OpenAI. Even those offered strong generative capabilities; what was not found in IBM watsonx.ai were the several enterprise attributes that were …
    Incentivized
    Chose IBM watsonx.ai
    About the same features, but these two require extensions and plug-ins to have the same functionalities
    Incentivized
    OpenAI
    Chose OpenAI API Platform
    Due to in part of difficult situation, OpenAI recognizes me as a researcher and supports my projects.
    Incentivized
    Key User Insights
    Would buy again
    100%
    Would buy again
    14 Answers
    No answers on this topic
    Delivers good value for the price
    100%
    Delivers good value for the price
    12 Answers
    No answers on this topic
    Happy with the feature set
    100%
    Happy with the feature set
    14 Answers
    No answers on this topic
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    13 Answers
    No answers on this topic
    Implementation went as expected
    100%
    Implementation went as expected
    14 Answers
    No answers on this topic
    Best Alternatives
    IBM watsonx.aiOpenAI API Platform
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    Score8.2 out of 10
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    Enterprises
    DataRobot
    Score8.2 out of 10
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    User Ratings
    IBM watsonx.aiOpenAI API Platform
    Likelihood to Recommend
    8.2
    (8 ratings)
    10.0
    (2 ratings)
    Usability
    7.7
    (4 ratings)
    10.0
    (1 ratings)
    User Testimonials
    IBM watsonx.aiOpenAI API Platform
    Likelihood to Recommend
    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.
    Incentivized
    Read full review
    OpenAI
    For smaller organizations that run lean and would like to get to deploy a solution quickly. This is a solution that is easy and quick to develop. It has a good amount of customization. However, for advanced customization this might not be a good solution. I suggest experimenting with OpenAI API and then if the experimentation is successful then it is a good idea to optimize and try other LLM models.
    Incentivized
    Read full review
    Pros
    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.
    Incentivized
    Read full review
    OpenAI
    • The developer experience is top notch. Their SDKs are super easy to use
    • Organization and project billing separation. You know where everything was consumed.
    • Playground. The playground is super useful to prototype without writing a single line of code
    Incentivized
    Read full review
    Cons
    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
    Incentivized
    Read full review
    OpenAI
    • Restrictions are sometimes too strong
    Incentivized
    Read full review
    Likelihood to Renew
    IBM
    its a future
    Incentivized
    Read full review
    OpenAI
    No answers on this topic
    Usability
    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.
    Incentivized
    Read full review
    OpenAI
    Easy to setup, develop and deploy. The payload for the API is simple and has all the inputs required for simple projects. There are a good number of options of LLM models to optimize for speed, cost or quality of the answers. A larger token input might improve the overall usability.
    Incentivized
    Read full review
    Alternatives Considered
    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.
    Incentivized
    Read full review
    OpenAI
    Anthropic is only the best for coding and its really really expensive. So, if you're not making a coding app, I would stay away from it. On the other hand, Gemini models are dirt cheap but come with a bit of performance limitations, so i would use it for big volume non sofisticated use cases. The OpenAI API platform excels at providing best in class performance models, at not outrageous anthropic-like pricing.
    Incentivized
    Read full review
    Return on Investment
    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
    Incentivized
    Read full review
    OpenAI
    • Big question about functionality
    Incentivized
    Read full review
    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.