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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Vertex AI

    Score8.8 out of 10
    N/AVertex AI on Google Cloud is an MLOps solution, used to build, deploy, and scale machine learning (ML) models with fully managed ML tools for any use case.

    $0

    Starting at

    Hugging Face

    Score9.9 out of 10
    N/AHugging Face is an open-source provider of natural language processing (NLP) technologies.

    $9

    per month

    Pricing
    Vertex AIHugging Face
    Editions & Modules
    Imagen model for image generation
    $0.0001
    Starting at
    Text, chat, and code generation
    $0.0001
    per 1,000 characters
    Text data upload, training, deployment, prediction
    $0.05
    per hour
    Video data training and prediction
    $0.462
    per node hour
    Image data training, deployment, and prediction
    $1.375
    per node hour
    Pro Account
    $9
    per month
    Enterprise Hub
    $20
    per month per user
    Offerings
    Pricing Offerings
    Vertex AIHugging Face
    Free Trial
    YesNo
    Free/Freemium Version
    YesYes
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeOptionalNo setup fee
    Additional DetailsPricing is based on the Vertex AI tools and services, storage, compute, and Google Cloud resources used.
    More Pricing Information
    Community Pulse
    Vertex AIHugging Face
    Considered Both Products
    Google
    No answer on this topic
    Hugging Face
    No answer on this topic
    Key User Insights
    Would buy again
    No answers on this topic
    100%
    Would buy again
    6 Answers
    Delivers good value for the price
    No answers on this topic
    100%
    Delivers good value for the price
    6 Answers
    Happy with the feature set
    No answers on this topic
    100%
    Happy with the feature set
    6 Answers
    Lived up to sales and marketing promises
    No answers on this topic
    100%
    Lived up to sales and marketing promises
    6 Answers
    Implementation went as expected
    No answers on this topic
    100%
    Implementation went as expected
    6 Answers
    Best Alternatives
    Vertex AIHugging Face
    Small Businesses
    Saturn Cloud
    Score7.6 out of 10
    TensorFlow
    Score8.2 out of 10
    Medium-sized Companies
    DataRobot
    Score8.2 out of 10
    Google Cloud AI
    Score8.7 out of 10
    Enterprises
    DataRobot
    Score8.2 out of 10
    Google Cloud AI
    Score8.7 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    Vertex AIHugging Face
    Likelihood to Recommend
    6.7
    (10 ratings)
    9.4
    (6 ratings)
    Performance
    7.3
    (7 ratings)
    -
    (0 ratings)
    Configurability
    7.0
    (7 ratings)
    -
    (0 ratings)
    User Testimonials
    Vertex AIHugging Face
    Likelihood to Recommend
    Google
    Vertex AI seems to be a lot more accurate with image editing versus other competitors (including free one). We do a lot of image creation, especially of dogs in very certain scenarios. We use Adobe Stock to get us started, but many times we need some very specific edits done to the image. We've found Vertex can produce those with a lot more precision than other AI image generators.
    Incentivized
    Read full review
    Hugging Face
    If an organisation has more access to data and have access to high end computers like GPUs it’s recommended to use Hugging face as it will give better accuracy than any other models. If an organisation having less data and has less access to GPUsis looking for decent performance then traditional algorithms are more appropriate than hugging face
    Incentivized
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    Pros
    Google
    • Vertex AI comes with support for LOTs of LLMs out of the box
    • MLOps tools are available that help to standardize operational aspects
    • Document AI is an out of the box feature that works just perfectly for our use cases of automating lots to tedious data extraction tasks from images as well as papers
    Incentivized
    Read full review
    Hugging Face
    • Model APIs
    • Hugging Face Spaces for deploying demo apps
    • Latest updated models available easily
    • Vast support for language parsing and other relevant tasks
    Incentivized
    Read full review
    Cons
    Google
    • Customization of AutoML models - A must needed capability to be able to tweak hyperparameters and also working with different models
    • Model Explainability -Providing more comprehensive explanations about how models are utilizing features could be very beneficial
    • Model versioning and experiments tracking - Enhancing the versioning capability could be good for end users
    Incentivized
    Read full review
    Hugging Face
    • Most of the Hugging face models are of big size, hence difficult to work if there is no access to high computational system like GPU.
    • It’s good to have some visualization tool in hugging face for viewing model architecture.
    • I recommend to implement hugging face lite version so that it can run on any system with less specifications.
    Incentivized
    Read full review
    Performance
    Google
    It's not always instant, but understandable when it's under heavy load. It's not impressive nor disappointing, just what is expected. But when calling this platform through API's for it to do the actions requested there is minimal delay and wait time. It feels very responsive and quick when integrating it with a call center chat platform for example.
    Incentivized
    Read full review
    Hugging Face
    No answers on this topic
    Alternatives Considered
    Google
    Vertex AI is much more accessible to non-developers than IBM's product. Moreover, Vertex AI integrates well with other Google products, enhancing its capabilities. A big plus is its integration with cloud storage, that allows for better management and access of data. In all honesty, it wasn't much of a difficult choice to choose Vertex AI.
    Incentivized
    Read full review
    Hugging Face
    There are some other services offer similar capacity as to Hugging Face, but not entirely the same. For example, amazon web services have a machine learning service called Comprehend, which offer a set of easy to use APIs to do machine translation and entity recognition and some other common NLP use case.
    Incentivized
    Read full review
    Return on Investment
    Google
    • It is pay as you go model so it'll save more cost of your org. In our case previously we used to incurred 1-2L/Month now we are reduced it to 80k-1L.
    • It'll help you save your model training & model selection time as it provides pre-trained models in autoML.
    • It'll help you in terms of Security wherein we can use row level security access to authorized persons.
    Incentivized
    Read full review
    Hugging Face
    • Hugging Face is cost and time saving.
    • Pay is less, you pay what you use, doesn't affect much.
    • Overall positive impact on business.
    Incentivized
    Read full review
    ScreenShots

    Vertex AI Screenshots

    Screenshot of an introduction to generative AI on Vertex AI - Vertex AI Studio offers a Google Cloud console tool for rapidly prototyping and testing generative AI models.Screenshot of gen AI for summarization, classification, and extraction - Text prompts can be created to handle any number of tasks with Vertex AI’s generative AI support. Some of the most common tasks are classification, summarization, and extraction. Vertex AI’s PaLM API for text can be used to design prompts with flexibility in terms of their structure and format.Screenshot of Custom ML training overview and documentation - An overview of the custom training workflow in Vertex AI, the benefits of custom training, and the various training options that are available. This page also details every step involved in the ML training workflow from preparing data to predictions.Screenshot of ML model training and creation -  A guide that shows how Vertex AI’s AutoML is used to create and train custom machine learning models with minimal effort and machine learning expertise.Screenshot of deployment for batch or online predictions - When using a model to solve a real-world problem, the Vertex AI prediction service can be used for batch and online predictions.

    Hugging Face Screenshots

    Product screenshot