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Machine Learning · head to head

Keras vs Weka

Keras logo

Keras

Machine Learning

Deep learning API for humans

From
Free
Rated
-
Full reviewWebsite
Weka logo

Weka

Machine Learning

Collection of machine learning algorithms

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Keras limited customization compared to TensorFlow; advanced users may find constraints in complex model designs; Weka the package management system needs an internet connection to download and install packages, so an air-gapped install gets only the core distribution
  • They diverge on capability: Keras covers Sequential and Functional API, Weka covers Classification.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Keras and Weka actually diverge.

Attributes where Keras and Weka differ
AttributeKerasWeka
PlatformsPython, Google Colab, JupyterLinux, Mac, Windows
Founded20151993

Identical on both: starting price (Free), pricing model (open-source), free tier (Yes), user rating (Not yet rated), category (Machine Learning).

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 Keras

  • Sequential and Functional API
  • Pre-built neural network layers
  • Model training and evaluation
  • Transfer learning
  • Model serialization
  • TensorFlow
  • JAX
  • PyTorch

Only in Weka

  • Classification
  • Regression
  • Clustering
  • Association rules
  • Feature selection
  • Java
  • R
  • Python

Both cover

  • Linux support
  • Mac support
  • Windows support

What people use each for

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

Keras

  • Machine learningnot Weka
  • Data analysisnot Weka
  • Model trainingnot Weka
  • Predictive analyticsnot Weka

Weka

  • Teaching and exploring classic machine learning algorithms through a GUInot Keras
  • Running data mining experiments and preprocessing without writing codenot Keras

Where each one falls short

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

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

Weka

  • The package management system needs an internet connection to download and install packages, so an air-gapped install gets only the core distribution
  • Weka is split into a stable 3.8 branch that receives only bug fixes and compatibility-safe upgrades and a 3.9 development branch that may receive features that break compatibility
  • Weka requires a 64-bit Java VM; the bundled installers ship Bellsoft OpenJDK 25 per platform and architecture

Pricing, plan by plan

Keras

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

Weka

Free
  • Open SourceFree
    • All ML algorithms
    • GUI and CLI
    • Java API

Which should you pick?

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

Choose Weka if

  • You need classification.
  • You want to start without paying.
  • You work on Linux, Mac, Windows.
  • You also want regression.
Weka review

Questions people ask

Is Keras or Weka better?
Neither clearly leads. Keras starts at Free and Weka at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Keras or Weka?
Keras starts at Free and Weka at Free.
Does Keras or Weka run on more platforms?
Keras runs on Python, Google Colab, Jupyter. Weka runs on Linux, Mac, Windows.
Can I use Keras for free?
Both have a free tier, so you can try either at no cost before committing.
What is Keras best used for?
Keras is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Weka is typically brought in for.
What can Keras do that Weka cannot?
Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning. Weka covers Classification, Regression, Clustering, Association rules. Both handle Linux support, Mac support, Windows support.

Answered from the vendors’ own pages

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
Weka: What is the cost of Weka software?

Weka is provided at no cost as open-source software released under the GNU General Public License, making it freely available for download and use.

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
Weka: Are there commercial licensing options available?

Yes, the project offers information about commercial licenses for organizations requiring non-GPL terms, which can be found in their commercial applications documentation.

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
Weka: What support resources are available to users?

Multiple support avenues exist including comprehensive documentation, frequently asked questions, dedicated help resources, and access to courses for learning the platform.

Source
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.

Source
Weka: Is source code access provided?

Yes, developers have full access to source code through the Git repository, along with development documentation and code credits for contributors.

Source
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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