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Software · head to head

JMP vs PyTorch

JMP logo

JMP

Software

Statistical discovery software from SAS

From
Free
Rated
-
Full reviewWebsite
PyTorch logo

PyTorch

Software

Deep learning framework with dynamic computation graphs

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: JMP the Internet Archive's capture of JMP's homepage on 13 January 2020 named five distinct editions, JMP, JMP Live, JMP Pro, JMP Clinical, and JMP Genomics, each targeting a different analysis use case, with no price figure published for any.; PyTorch dynamic computation graph can be less efficient for production inference than static graphs
  • They diverge on capability: JMP covers Interactive statistics, PyTorch covers Dynamic computation graphs.

Where they differ

Only the attributes on which JMP and PyTorch actually diverge.

Attributes where JMP and PyTorch differ
AttributeJMPPyTorch
Pricing modelsubscriptionUnknown
PlatformsMac, WindowsLinux, Windows, macOS
Founded19762016

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Unknown).

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 JMP

  • Interactive statistics
  • Dynamic visualization
  • Design of experiments
  • Predictive modeling
  • Quality control
  • SAS
  • Python
  • R

Only in PyTorch

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

Both cover

  • Mac support
  • Windows support

What people use each for

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

JMP

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

PyTorch

  • 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.

JMP

  • The Internet Archive's capture of JMP's homepage on 13 January 2020 named five distinct editions, JMP, JMP Live, JMP Pro, JMP Clinical, and JMP Genomics, each targeting a different analysis use case, with no price figure published for any.

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

Pricing, plan by plan

JMP

Free
  • TrialFree
    • 30-day trial
    • Full features
  • JMP$1785/year
    • Core JMP
    • Standard features

PyTorch

Free

No published plan breakdown. See the PyTorch review.

Which should you pick?

Choose JMP if

  • You need interactive statistics.
  • You want to start without paying.
  • You work on Mac, Windows.
  • You also want dynamic visualization.
JMP review

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

Questions people ask

Is JMP or PyTorch better?
Neither clearly leads. JMP starts at Free and PyTorch at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, JMP or PyTorch?
JMP starts at Free and PyTorch at Free.
Does JMP or PyTorch run on more platforms?
JMP runs on Mac, Windows. PyTorch runs on Linux, Windows, macOS.
Can I use JMP for free?
Both have a free tier, so you can try either at no cost before committing.
What is JMP best used for?
JMP is most often used for machine learning, data analysis, model training, predictive analytics.
What can JMP do that PyTorch cannot?
JMP covers Interactive statistics, Dynamic visualization, Design of experiments, Predictive modeling. PyTorch covers Dynamic computation graphs, Automatic differentiation, GPU acceleration, Distributed training. Both handle 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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