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Machine Learning & Data Science · head to head

Google Vertex AI vs Keras

Google Vertex AI logo

Google Vertex AI

Machine Learning & Data Science

Unified ML platform to build, deploy, and scale AI models

From
On request
Rated
-
Full reviewWebsite
Keras logo

Keras

Machine Learning & Data Science

Deep learning API for humans

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only Keras has a free tier, so it costs nothing to try first.
  • Each has a real cost: Google Vertex AI vendor lock-in to Google Cloud ecosystem makes migration to other platforms difficult; Keras limited customization compared to TensorFlow; advanced users may find constraints in complex model designs
  • They diverge on capability: Google Vertex AI covers AutoML, Keras covers Sequential and Functional API.

Where they differ

Only the attributes on which Google Vertex AI and Keras actually diverge.

Attributes where Google Vertex AI and Keras differ
AttributeGoogle Vertex AIKeras
Starting priceOn requestFree
Pricing modelUnknownopen-source
Free tierNoYes
PlatformsCloud, WebPython, Google Colab, Jupyter
Founded20082015

Identical on both: user rating (Not yet rated), category (Machine Learning & Data Science).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Google Vertex AI

  • AutoML
  • Custom training
  • Feature Store
  • Model monitoring
  • Prediction serving
  • BigQuery
  • Cloud Storage
  • Dataflow

Only in Keras

  • Sequential and Functional API
  • Pre-built neural network layers
  • Model training and evaluation
  • Transfer learning
  • Model serialization
  • JAX
  • Linux support
  • Mac support

Both cover

  • TensorFlow
  • PyTorch

What people use each for

The jobs each tool is most often brought in to do.

Google Vertex AI

  • Machine learning
  • Data analysis
  • Model training
  • Predictive analytics

Keras

  • Machine learning
  • Data analysis
  • Model training
  • Predictive analytics

Both are used for machine learning, data analysis, model training, predictive analytics, on those jobs the choice comes down to price and fit rather than capability.

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Google Vertex AI

  • Vendor lock-in to Google Cloud ecosystem makes migration to other platforms difficult
  • Requires familiarity with Google Cloud Platform infrastructure and concepts
  • Cost can escalate quickly with large training and inference workloads

Keras

  • Limited customization compared to TensorFlow; advanced users may find constraints in complex model designs
  • Error messages can be vague and unhelpful, making debugging challenging
  • Smaller ecosystem and fewer pre-trained models than TensorFlow or PyTorch

Pricing, plan by plan

Google Vertex AI

On request

No published plan breakdown. See the Google Vertex AI review.

Keras

Free
  • Open SourceFree
    • High-level API
    • Pre-built layers
    • Model serialization

Which should you pick?

Choose Google Vertex AI if

  • You need automl.
  • You work on Cloud, Web.
  • You also want custom training.
Google Vertex AI review

Choose Keras if

  • You need sequential and functional api.
  • You want to start without paying.
  • You work on Python, Google Colab, Jupyter.
  • You also want pre-built neural network layers.
Keras review

Questions people ask

Is Google Vertex AI or Keras better?
Neither clearly leads. Google Vertex AI starts at On request and Keras at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Google Vertex AI or Keras?
Keras has a free tier; the other does not. Paid plans start at On request for Google Vertex AI and Free for Keras.
Does Google Vertex AI or Keras run on more platforms?
Google Vertex AI runs on Cloud, Web. Keras runs on Python, Google Colab, Jupyter.
Can I use Keras for free?
Yes. Keras has a free tier, so you can try it without paying. Google Vertex AI starts at On request.
What is Google Vertex AI best used for?
Google Vertex AI is most often used for machine learning, data analysis, model training, predictive analytics.
What can Google Vertex AI do that Keras cannot?
Google Vertex AI covers AutoML, Custom training, Feature Store, Model monitoring. Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning. Both handle TensorFlow, PyTorch.

Answered from the vendors’ own pages

Google Vertex AI: What is the pricing model for Google Vertex AI?

Vertex AI uses a pay-as-you-go model with no upfront costs or lock-in fees. Costs vary by service: training is billed by compute resources and time (30-second increments), online predictions by machine type per hour, and batch predictions by compute time or per-record for specific AutoML types.

Source
Keras: What is Keras?

Keras is a high-level deep learning API built on top of TensorFlow that simplifies building and training neural networks. Keras 3 supports multiple backends including TensorFlow, PyTorch, and JAX, making it backend-agnostic.

Source
Google Vertex AI: What types of data can Vertex AI handle?

Vertex AI supports image, video, text, and tabular data types with tools for uploading, storing, and managing large datasets.

Source
Keras: What model architectures does Keras support?

Keras supports the Sequential model for linear stacks of layers, the Functional API for arbitrary graph architectures, and model subclassing for custom implementations. All approaches provide access to layers, optimizers, metrics, and callbacks.

Source
Google Vertex AI: Does Vertex AI support custom model training?

Yes. Vertex AI supports both AutoML for automated machine learning and custom training code in Python, R, and other languages.

Source
Keras: Can Keras models run on TPUs and GPUs?

Yes, Keras models can run on TPU Pods or large GPU clusters, be exported to run in browsers or on mobile devices, and be served via web APIs.

Source
Google Vertex AI: What deployment options are available in Vertex AI?

Vertex AI supports online predictions for real-time use cases and batch predictions for large-scale processing.

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Keras: Does Keras offer pre-trained models?

Yes, Keras provides pre-trained models through KerasHub and Keras Applications for common deep learning tasks like image classification, object detection, and NLP.

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Keras: Who should use Keras?

Keras is ideal for beginners and rapid prototyping due to its simplicity and user-friendly interface. Advanced users and production deployments may benefit more from lower-level frameworks like TensorFlow or PyTorch for greater customization.

Source
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