Machine Learning · head to head
Keras vs Stata

Stata
Machine Learning
Data science software for research professionals
- From
- $48/year
- Rated
- -
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; Stata the entry Stata/BE edition is capped at 2,048 variables and 798 independent variables in a model
- They diverge on capability: Keras covers Sequential and Functional API, Stata covers Statistical analysis.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Keras and Stata actually diverge.
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 Stata
- Statistical analysis
- Data management
- Graphics
- Econometrics
- Survey analysis
- Python
- ODBC
- Excel
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 Stata
- Data analysisnot Stata
- Model trainingnot Stata
- Predictive analyticsnot Stata
Stata
- Statistical analysis and data analysisnot Keras
- Econometric modelingnot Keras
- Biostatistics and epidemiologynot Keras
- Academic and research data analysisnot 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
Stata
- The entry Stata/BE edition is capped at 2,048 variables and 798 independent variables in a model
- Raising the variable limit to 32,767 requires Stata/SE and 120,000 requires Stata/MP
- Stata/MP is licensed by core count, so 2 core and 4 core licences are priced separately
- Student licences require proof of enrolment at a degree granting institution
- Stata/MP is not sold on a 6 month student term
- Perpetual student licences cost several times the annual price, for example $298 against $94 for Stata/BE
Pricing, plan by plan
Keras
Free- Open SourceFree
- High-level API
- Pre-built layers
- Model serialization
Stata
$48/year- Stata/BE$48/year
- Basic edition
- Core features
- Stata/SE$295/year
- Standard edition
- Larger datasets
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.
Choose Stata if
- You need statistical analysis.
- You work on Linux, Mac, Windows.
- You also want data management.
Questions people ask
- Is Keras or Stata better?
- Neither clearly leads. Keras starts at Free and Stata at $48/year, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Keras or Stata?
- Keras has a free tier; the other does not. Paid plans start at Free for Keras and $48/year for Stata.
- Does Keras or Stata run on more platforms?
- Keras runs on Python, Google Colab, Jupyter. Stata runs on Linux, Mac, Windows.
- Can I use Keras for free?
- Yes. Keras has a free tier, so you can try it without paying. Stata starts at $48/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 Stata is typically brought in for.
- What can Keras do that Stata cannot?
- Keras covers Sequential and Functional API, Pre-built neural network layers, Model training and evaluation, Transfer learning. Stata covers Statistical analysis, Data management, Graphics, Econometrics. 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.
SourceStata: How much does Stata cost?
Stata does not publish specific pricing on its website. Customers must use the 'Order Stata' or 'Request a quote' functions to obtain pricing. StataNow is available as a subscription option, but specific monthly or annual costs are not displayed publicly.
SourceKeras: 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.
SourceStata: What are the differences between Stata editions?
Stata offers multiple editions including Stata/BE and Stata/MP, with different capabilities and performance characteristics. Edition selection affects pricing, but specific comparisons and costs require requesting a quote.
SourceKeras: 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.
SourceStata: Does Stata offer a subscription model?
Yes, StataNow is offered as a subscription option that delivers new features immediately upon release. However, specific pricing for StataNow subscriptions is not published on the website.
SourceKeras: 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.
SourceKeras: 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.
SourceRelated pages
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- Stata vs ClearML
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- Stata vs Databricks
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