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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    Amazon SageMaker

    Score8.2 out of 10
    N/AAmazon SageMaker enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. Amazon SageMaker removes all the barriers that typically slow down developers who want to use machine learning.N/A

    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

    Pricing
    Amazon SageMakerVertex AI
    Editions & Modules
    No answers on this topic
    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
    Offerings
    Pricing Offerings
    Amazon SageMakerVertex AI
    Free Trial
    NoYes
    Free/Freemium Version
    NoYes
    Premium Consulting/Integration Services
    NoNo
    Entry-level Setup FeeNo setup feeOptional
    Additional DetailsPricing is based on the Vertex AI tools and services, storage, compute, and Google Cloud resources used.
    More Pricing Information
    Community Pulse
    Amazon SageMakerVertex AI
    Considered Both Products
    Amazon AWS
    No answer on this topic
    Google
    Chose Vertex AI
    I have used AWS sagemaker is the past for AI/ML model development in my previous organization for everything. Sagemaker is good with respect to certain services but when we talk about Vertex AI in comparison, AutoML is the differentiator. AutoML is very strong and is able to …
    Incentivized
    Key User Insights
    Would buy again
    No answers on this topic
    No answers on this topic
    Delivers good value for the price
    No answers on this topic
    No answers on this topic
    Happy with the feature set
    No answers on this topic
    No answers on this topic
    Lived up to sales and marketing promises
    No answers on this topic
    No answers on this topic
    Implementation went as expected
    No answers on this topic
    No answers on this topic
    User Ratings
    Amazon SageMakerVertex AI
    Likelihood to Recommend
    9.0
    (5 ratings)
    6.7
    (10 ratings)
    Performance
    -
    (0 ratings)
    7.3
    (7 ratings)
    Configurability
    -
    (0 ratings)
    7.0
    (7 ratings)
    User Testimonials
    Amazon SageMakerVertex AI
    Likelihood to Recommend
    Amazon AWS
    It allows for one-click processes and for things to be auto checked before they are moved through the process but through the system. It also makes training easy. I am able to train users on the basic fundamentals of the tool and how it is used very easily as it is fully managed on its own which is incredible.
    Incentivized
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    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
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    Pros
    Amazon AWS
    • Machine Learning at scale by deploying huge amount of training data
    • Accelerated data processing for faster outputs and learnings
    • Kubernetes integration for containerized deployments
    • Creating API endpoints for use by technical users
    Incentivized
    Read full review
    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
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    Cons
    Amazon AWS
    • It's very good for the hardcore programmer, but a little bit complex for a data scientist or new hire who does not have a strong programming background.
    • Most of the popular library and ML frameworks are there, but we still have to depend on them for new releases.
    Incentivized
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    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
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    Performance
    Amazon AWS
    No answers on this topic
    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
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    Alternatives Considered
    Amazon AWS
    Amazon SageMaker took the heavy lifting out of building and creating models. It allowed for our organization to use our current system for integration and essentially added on a feature to help all levels of Data scientists and IT professionals in our department and company as a whole. The training was simple as well.
    Incentivized
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    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
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    Return on Investment
    Amazon AWS
    • We have been able to deliver data products more rapidly because we spend less time building data pipelines and model servers.
    • We can prototype more rapidly because it is easy to configure notebooks to access AWS resources.
    • For our use-cases, serving models is less expensive with SageMaker than bespoke servers.
    Incentivized
    Read full review
    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
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    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.