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Machine Learning & Data Science · head to head

PyTorch vs Weka

PyTorch logo

PyTorch

Machine Learning & Data Science

Deep learning framework with dynamic computation graphs

From
Free
Rated
-
Full reviewWebsite
Weka logo

Weka

Machine Learning & Data Science

Collection of machine learning algorithms

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: PyTorch dynamic computation graph can be less efficient for production inference than static graphs; 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: PyTorch covers Dynamic computation graphs, Weka covers Classification.

Where they differ

Only the attributes on which PyTorch and Weka actually diverge.

Attributes where PyTorch and Weka differ
AttributePyTorchWeka
Pricing modelUnknownopen-source
PlatformsLinux, Windows, macOSLinux, Mac, Windows
Founded20161993

Identical on both: starting price (Free), free tier (Yes), 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 PyTorch

  • Dynamic computation graphs
  • Automatic differentiation
  • GPU acceleration
  • Distributed training
  • TorchScript
  • TorchVision
  • TorchText
  • TorchAudio

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.

PyTorch

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

Weka

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

Where each one falls short

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

PyTorch

  • Dynamic computation graph can be less efficient for production inference than static graphs
  • Requires more manual code for distributed training compared to some alternatives
  • Documentation focused heavily on research use cases rather than production deployment

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

PyTorch

Free

No published plan breakdown. See the PyTorch review.

Weka

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

Which should you pick?

Choose PyTorch if

  • You need dynamic computation graphs.
  • You want to start without paying.
  • You work on Linux, Windows, macOS.
  • You also want automatic differentiation.
PyTorch 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 PyTorch or Weka better?
Neither clearly leads. PyTorch 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, PyTorch or Weka?
PyTorch starts at Free and Weka at Free.
Does PyTorch or Weka run on more platforms?
PyTorch runs on Linux, Windows, macOS. Weka runs on Linux, Mac, Windows.
Can I use PyTorch for free?
Both have a free tier, so you can try either at no cost before committing.
What is PyTorch best used for?
PyTorch 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 PyTorch do that Weka cannot?
PyTorch covers Dynamic computation graphs, Automatic differentiation, GPU acceleration, Distributed training. Weka covers Classification, Regression, Clustering, Association rules. Both handle Linux support, Mac support, Windows support.

Answered from the vendors’ own pages

PyTorch: Is PyTorch free and open source?

Yes. PyTorch is an open source machine learning framework that is completely free to use. It was originally created and open-sourced by Facebook (now Meta) in 2016.

Source
PyTorch: What platforms does PyTorch support?

PyTorch supports Linux, Windows, and macOS. It provides strong GPU acceleration through CUDA and other backends for high-performance computing.

Source
PyTorch: Can I use PyTorch for production deployments?

Yes. PyTorch provides graph-based execution, distributed training, mobile deployment, and quantization features to support production deployments.

Source
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