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Machine Learning · head to head

Keras vs Minitab

Keras logo

Keras

Machine Learning

Deep learning API for humans

From
Free
Rated
-
Full reviewWebsite
Minitab logo

Minitab

Machine Learning

Statistical software for quality engineering, and the tool Six Sigma training is written around

From
$2394/year
Rated
-
Full reviewWebsite

The short version

  • Only Keras has a free tier, so it costs nothing to try first.
  • Each has a real cost: Keras limited customization compared to TensorFlow; advanced users may find constraints in complex model designs; Minitab licensing is a per named user subscription, so an organisation where fifty engineers each need it twice a quarter pays fifty full seats for people who open it eight times a year.
  • They diverge on capability: Keras covers Sequential and Functional API, Minitab covers Control charts.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Keras and Minitab actually diverge.

Attributes where Keras and Minitab differ
AttributeKerasMinitab
Starting priceFree$2394/year
Pricing modelopen-sourcesubscription
Free tierYesNo
PlatformsPython, Google Colab, JupyterMac, Windows, Web
Founded20151972

Identical on both: 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 Minitab

  • Control charts
  • Process capability analysis
  • Measurement systems analysis
  • Design of experiments
  • Classical statistics
  • Assistant
  • Predictive Analytics module
  • Desktop and browser access

What people use each for

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

Keras

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

Minitab

  • Six Sigma and process improvement projects where the training materials and internal procedures already assume Minitabnot Keras
  • Producing capability and gage studies as evidence for a customer audit or a regulatory submissionnot Keras
  • Design of experiments on a production process, run by an engineer who will not be writing codenot Keras
  • Quality departments that need credible statistics without hiring a statistician or a data scientistnot 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

Minitab

  • Licensing is a per named user subscription, so an organisation where fifty engineers each need it twice a quarter pays fifty full seats for people who open it eight times a year.
  • Analyses are recorded as a project file and a session log rather than as code, so reviewing what somebody did means reading output instead of reading a script, and reproducing it a year later depends on the same version still being installed.
  • The machine learning capability is a separately licensed module with a fixed set of tree-based methods, so it is neither included in the base price nor competitive with what a Python user has for nothing.
  • There is no deployment path in the statistical product, so putting a model into a running process means buying Minitab Model Ops as another product or reimplementing the model somewhere else entirely.
  • Data handling is worksheet-shaped and held in memory, so anything past a few million rows means preparing the extract in another tool first, and joins and reshaping are clumsy compared with SQL or pandas.

Pricing, plan by plan

Keras

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

Minitab

$2394/year
  • Solution Center Core$2394/year
    • Marked as Most Popular
    • Best for quality professionals
    • Minitab Dashboards
  • Solution Center Analytics$2593.5/year
    • Best for analytics professionals
    • Includes predictive analytics capabilities
    • Minitab Dashboards
  • Solution Center Copilot$2793/year
    • All-in-one platform for operational excellence
    • Includes AI-powered insights
    • Minitab Dashboards

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 Minitab if

  • You need control charts.
  • You work on Mac, Windows, Web.
  • You also want process capability analysis.
Minitab review

Questions people ask

Is Keras or Minitab better?
Neither clearly leads. Keras starts at Free and Minitab at $2394/year, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Keras or Minitab?
Keras has a free tier; the other does not. Paid plans start at Free for Keras and $2394/year for Minitab.
Does Keras or Minitab run on more platforms?
Keras runs on Python, Google Colab, Jupyter. Minitab runs on Mac, Windows, Web.
Can I use Keras for free?
Yes. Keras has a free tier, so you can try it without paying. Minitab starts at $2394/year.
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 Minitab is typically brought in for.
What can Keras do that Minitab cannot?
Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning. Minitab covers Control charts, Process capability analysis, Measurement systems analysis, Design of experiments.

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
Minitab: Does Minitab run on macOS?

The installed desktop application is Windows. Mac users work through the browser version, which is included with the subscription but is not identical in every feature.

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
Minitab: Is it machine learning software?

Not primarily. It is a statistics package for quality and process work. Predictive modelling exists in a separate Predictive Analytics module and is limited to tree-based methods.

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
Minitab: Can I buy a perpetual licence?

The current offer is subscription based. Older perpetual licences exist in the field but are not the way the product is sold now.

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
Minitab: What is the difference between Minitab and Minitab Workspace or Engage?

Minitab Statistical Software does the analysis. Workspace and Engage are separate products for process mapping, project management and improvement programme governance, and are licensed separately.

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
Minitab: Can I automate it?

Only to a limited degree. There is a command language and integration options, but it is designed to be driven by a person through menus, not scheduled in a pipeline.

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