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Augment Code vs scikit-learn

Augment Code logo

Augment Code

Software Development

Agentic software development at organizational scale

From
$100/month
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: Augment Code enterprise requires custom pricing negotiation; scikit-learn no GPU acceleration by default; limited optional GPU support requires external arrays

Where they differ

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

Attributes where Augment Code and scikit-learn differ
AttributeAugment Codescikit-learn
Starting price$100/monthFree
Pricing modelsubscriptionUnknown
Free tierNoYes
PlatformsWebPython, 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 Augment Code

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.

Augment Code

  • AI-powered code completionnot scikit-learn
  • Development tool integrationnot scikit-learn
  • Enterprise software developmentnot scikit-learn

scikit-learn

  • Machine learningnot Augment Code
  • Data analysisnot Augment Code
  • Model trainingnot Augment Code
  • Predictive analyticsnot Augment Code

Where each one falls short

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

Augment Code

  • Enterprise requires custom pricing negotiation
  • Usage allowance only covers $100/month; overages charge 40% service fee on provider rates

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

Augment Code

$100/month
  • Business$100/month
    • Up to 50 seats
    • $100 monthly usage allowance
    • Cosmos access
  • Enterprise$null/month
    • Custom pricing
    • Custom user pricing and usage limits
    • Unlimited concurrent sessions

scikit-learn

Free

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

Which should you pick?

Choose Augment Code if

Nothing in the data separates Augment Code from scikit-learn on the points above - pick on price and on how each one feels to use.

Augment Code 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 Augment Code or scikit-learn better?
Neither clearly leads. Augment Code starts at $100/month and scikit-learn at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Augment Code or scikit-learn?
scikit-learn has a free tier; the other does not. Paid plans start at $100/month for Augment Code and Free for scikit-learn.
Does Augment Code or scikit-learn run on more platforms?
Augment Code runs on 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. Augment Code starts at $100/month.
What is Augment Code best used for?
Augment Code is most often used for ai-powered code completion, development tool integration, enterprise software development. Of those, ai-powered code completion and development tool integration are not what scikit-learn is typically brought in for.
What can Augment Code do that scikit-learn cannot?
scikit-learn covers Classification algorithms, Regression models, Clustering methods, Dimensionality reduction.

Answered from the vendors’ own pages

Augment Code: How much does Augment Code Business plan cost?

Augment Code Business plan is $100 per month with no per-seat charges, includes up to 50 seats, and provides $100 in monthly usage allowance pooled across the team.

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
Augment Code: How does Augment Code usage billing work?

The Business plan includes $100 monthly usage measured in dollars across LLM inference (billed at provider rates plus 40% service fee) and compute time. Usage is pooled across the entire team. Top-ups expire 12 months after purchase.

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
Augment Code: What does Augment Code Enterprise include?

Enterprise plan includes all Business features plus custom user pricing, bespoke usage limits, volume-based annual discounts, unlimited concurrent sessions, multi-region compute, custom compute size, SSO/OIDC/SCIM support, and CMEK and ISO 42001 compliance.

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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