Softwr

Machine Learning · head to head

scikit-learn vs Sourcegraph Cody

scikit-learn logo

scikit-learn

Machine Learning

Machine learning in Python

From
Free
Free plan
Yes
Full reviewWebsite
Sourcegraph Cody logo

Sourcegraph Cody

AI

Enterprise AI coding assistant with whole-codebase context

From
$59/month
Free plan
No
Full reviewWebsite

The short version

  • Only scikit-learn has a free tier, so it costs nothing to try first.
  • Each has a real cost: scikit-learn no GPU acceleration by default; limited optional GPU support requires external arrays; Sourcegraph Cody no longer available to individual developers or small teams after free and Pro tiers were discontinued in mid-2025
  • They diverge on capability: scikit-learn covers Classification algorithms, Sourcegraph Cody covers Multi-repository context.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where scikit-learn and Sourcegraph Cody differ
Attributescikit-learnSourcegraph Cody
Starting priceFree$59/month
Pricing modelUnknownquote
Free tierYesNo
PlatformsPython, Linux, macOS, Windowsweb, windows, mac, linux
CategoryMachine LearningAI
Founded20072013

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 scikit-learn

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

Only in Sourcegraph Cody

  • Multi-repository context
  • Large context window
  • Context filters
  • Model flexibility
  • IDE integration

What people use each for

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

scikit-learn

  • Machine learningnot Sourcegraph Cody
  • Data analysisnot Sourcegraph Cody
  • Model trainingnot Sourcegraph Cody
  • Predictive analyticsnot Sourcegraph Cody

Sourcegraph Cody

  • Cross-repository code understanding for large engineering orgsnot scikit-learn
  • AI-assisted code review and refactoring at enterprise scalenot scikit-learn
  • Enforcing data-boundary controls when using third-party LLMsnot scikit-learn
  • Codebase-aware chat and autocomplete for developersnot scikit-learn

Where each one falls short

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

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

Sourcegraph Cody

  • No longer available to individual developers or small teams after free and Pro tiers were discontinued in mid-2025
  • Priced substantially higher than many competing AI coding assistants, with Enterprise plans typically requiring annual contracts
  • Sourcegraph has shifted its individual-developer focus to a separate product, Amp, creating uncertainty about Cody's long-term product priority
  • Requires integration with Sourcegraph's broader code intelligence platform rather than working as a lightweight standalone extension

Pricing, plan by plan

scikit-learn

Free

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

Sourcegraph Cody

$59/month
  • Enterprise$59/month
    • Whole-codebase AI context
    • Context filters for sensitive code
    • Multi-repository analysis

Which should you pick?

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

Choose Sourcegraph Cody if

  • You need multi-repository context.
  • You work on web, windows, mac, linux.
  • You also want large context window.
Sourcegraph Cody review

Questions people ask

Is scikit-learn or Sourcegraph Cody better?
Neither clearly leads. scikit-learn starts at Free and Sourcegraph Cody at $59/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, scikit-learn or Sourcegraph Cody?
scikit-learn has a free tier; the other does not. Paid plans start at Free for scikit-learn and $59/month for Sourcegraph Cody.
Does scikit-learn or Sourcegraph Cody run on more platforms?
scikit-learn runs on Python, Linux, macOS, Windows. Sourcegraph Cody runs on web, windows, mac, linux.
Can I use scikit-learn for free?
Yes. scikit-learn has a free tier, so you can try it without paying. Sourcegraph Cody starts at $59/month.
What is scikit-learn best used for?
scikit-learn is most often used for machine learning, data analysis, model training, predictive analytics. Of those, machine learning and data analysis are not what Sourcegraph Cody is typically brought in for.
What can scikit-learn do that Sourcegraph Cody cannot?
scikit-learn covers Classification algorithms, Regression models, Clustering methods, Dimensionality reduction. Sourcegraph Cody covers Multi-repository context, Large context window, Context filters, Model flexibility.

Answered from the vendors’ own pages

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
Sourcegraph Cody: Is Sourcegraph Cody still available to individual developers?

No, as of mid-2025 Cody Free and Pro plans were discontinued; Cody is now sold only as part of Sourcegraph's Enterprise plan, which requires an annual contract.

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
Sourcegraph Cody: How much does Sourcegraph Enterprise cost?

Enterprise plans start around $16,000 and scale with team size and seat count, including bundled AI credits; exact pricing requires a sales quote.

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
Sourcegraph Cody: How does the AI credit system work on Enterprise plans?

Each plan includes a pooled allocation of AI credits shared across the organization; credits do not expire and roll over at renewal, with volume credit add-ons available.

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
Sourcegraph Cody: What happens if my organization exceeds its credit allocation?

Sourcegraph's pricing page addresses overage and offers additional volume credit buckets for teams that need more than their committed allocation.

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
Sourcegraph Cody: Is a free trial available for Sourcegraph Enterprise?

Sourcegraph's pricing page lists free trial availability as one of its published FAQ topics for prospective Enterprise customers.

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
Share

Related pages

More on scikit-learn

More on Sourcegraph Cody

Keep looking

Other head to heads