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Devin vs scikit-learn

Devin logo

Devin

Software Development

Autonomous AI software engineer planning and executing code in its own environment

From
On request
Rated
-
Full reviewWebsite
scikit-learn logo

scikit-learn

Machine Learning

Machine learning in Python

From
Free
Rated
-
Full reviewWebsite

The short version

  • Only scikit-learn has a free tier, so it costs nothing to try first.
  • Each has a real cost: Devin pricing not published; specific costs and plan tiers require signup or contact with sales; scikit-learn no GPU acceleration by default; limited optional GPU support requires external arrays

Where they differ

Only the attributes on which Devin and scikit-learn actually diverge.

Attributes where Devin and scikit-learn differ
AttributeDevinscikit-learn
Starting priceOn requestFree
Pricing modelsubscriptionUnknown
Free tierNoYes
PlatformsDesktop, Windsurf integration, WebPython, Linux, macOS, Windows
CategorySoftware DevelopmentMachine Learning
FoundedUnknown2007

Identical on both: user rating (Not yet rated).

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 Devin

Nothing recorded that scikit-learn does not also cover.

Only in scikit-learn

  • Classification algorithms
  • Regression models
  • Clustering methods
  • Dimensionality reduction
  • Model selection
  • NumPy
  • SciPy
  • Pandas

What people use each for

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

Devin

  • Feature implementation and ticket resolution in established codebasesnot scikit-learn
  • Code migrations and refactoring at scale across repositoriesnot scikit-learn
  • Bug fixing and debugging with test-driven verificationnot scikit-learn
  • Rapid prototyping and proof-of-concept developmentnot scikit-learn
  • Repetitive implementation tasks freeing human engineers for complex designnot scikit-learn

scikit-learn

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

Where each one falls short

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

Devin

  • Pricing not published; specific costs and plan tiers require signup or contact with sales
  • Cannot handle extremely difficult tasks reliably; success rate decreases with task complexity
  • Requires clear, well-scoped task descriptions; ambiguous requirements reduce effectiveness
  • Requires human oversight and integration into existing workflows; not fully autonomous

scikit-learn

  • No GPU acceleration by default; limited optional GPU support requires external arrays
  • Single-machine only; no built-in distributed computing across clusters
  • All datasets must fit entirely in RAM; no out-of-core learning
  • No production-grade deep learning; neural network support limited to basic multilayer perceptron
  • No reinforcement learning algorithms

Pricing, plan by plan

Devin

On request

No published plan breakdown. See the Devin review.

scikit-learn

Free

No published plan breakdown. See the scikit-learn review.

Which should you pick?

Choose Devin if

  • You work on Desktop, Windsurf integration, Web.
Devin review

Choose scikit-learn if

  • You need classification algorithms.
  • You want to start without paying.
  • You work on Python, Linux, macOS, Windows.
  • You also want regression models.
scikit-learn review

Questions people ask

Is Devin or scikit-learn better?
Neither clearly leads. Devin starts at On request and scikit-learn at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Devin or scikit-learn?
scikit-learn has a free tier; the other does not. Paid plans start at On request for Devin and Free for scikit-learn.
Does Devin or scikit-learn run on more platforms?
Devin runs on Desktop, Windsurf integration, Web. scikit-learn runs on Python, Linux, macOS, Windows.
Can I use scikit-learn for free?
Yes. scikit-learn has a free tier, so you can try it without paying. Devin starts at On request.
What is Devin best used for?
Devin is most often used for feature implementation and ticket resolution in established codebases, code migrations and refactoring at scale across repositories, bug fixing and debugging with test-driven verification, rapid prototyping and proof-of-concept development. Of those, feature implementation and ticket resolution in established codebases and code migrations and refactoring at scale across repositories are not what scikit-learn is typically brought in for.
What can Devin do that scikit-learn cannot?
scikit-learn covers Classification algorithms, Regression models, Clustering methods, Dimensionality reduction.

Answered from the vendors’ own pages

Devin: What does Devin cost?

Devin's pricing is not publicly listed on their website. Interested parties must request a demo to discuss pricing and availability.

Source
scikit-learn: Does scikit-learn support GPU acceleration?

Scikit-learn has no native GPU support by design to keep installation simple and cross-platform. Since 2023, a limited number of estimators can run on GPUs if input data is provided as PyTorch or CuPy arrays, but this requires additional setup.

Source
Devin: How do I get access to Devin?

Devin is accessed by requesting a demo. There is no information about self-service signup, trial, or pricing on the public website.

Source
scikit-learn: Can scikit-learn handle datasets larger than RAM?

No. Scikit-learn is built on NumPy which requires all data to fit in memory, and NumPy operates on single-machine CPUs only. For very large datasets, consider Spark MLlib or distributed alternatives.

Source
scikit-learn: Is scikit-learn free to use commercially?

Yes. Scikit-learn is open source under the BSD license, which allows free commercial use, modification, and distribution.

Source
scikit-learn: What neural network capabilities does scikit-learn have?

Scikit-learn includes only a basic multilayer perceptron (MLPClassifier and MLPRegressor) for simple feedforward networks. For serious deep learning, use PyTorch, TensorFlow, or Keras instead.

Source
scikit-learn: Does scikit-learn include natural language processing?

Scikit-learn has minimal NLP support limited to basic text feature extraction and vectorization. For comprehensive text processing, use spaCy or NLTK instead.

Source
scikit-learn: When was scikit-learn first released?

Scikit-learn's first public release was February 1, 2010, following its start as a Google Summer of Code project in 2007.

Source
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