Comparison
Auto-PyTorch vs auto-sklearn
Verdict
Pick Auto-PyTorch if auto-PyTorch specializes in automatic architecture search and hyperparameter optimization for deep-learning models using PyTorch; pick auto-sklearn if auto-sklearn is an automated machine learning toolkit designed to automate hyperparameter optimization and function seamlessly with scikit-learn workflows.
Markdown twin · Auto-PyTorch alternatives · auto-sklearn alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | Auto-PyTorch | auto-sklearn |
|---|---|---|
| Maintenance | Dormant (846d since push) As of 3w · github_public_v1 | Steady (35d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization account As of 3w · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | Published findings As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- Auto-PyTorch
- Automatic architecture search and hyperparameter optimization for PyTorch
- auto-sklearn
- Automated Machine Learning with scikit-learn
Stars
- Auto-PyTorch
- 2.5k
- auto-sklearn
- 8.1k
Forks
- Auto-PyTorch
- 303
- auto-sklearn
- 1.3k
Open issues
- Auto-PyTorch
- 75
- auto-sklearn
- 209
Language
- Auto-PyTorch
- Python
- auto-sklearn
- Python
Adopt for
- Auto-PyTorch
- Auto-PyTorch specializes in automatic architecture search and hyperparameter optimization for deep-learning models using PyTorch.
- auto-sklearn
- auto-sklearn is an automated machine learning toolkit designed to automate hyperparameter optimization and function seamlessly with scikit-learn workflows.
Persona
- Auto-PyTorch
- -
- auto-sklearn
- -
Runtime
- Auto-PyTorch
- -
- auto-sklearn
- -
License
- Auto-PyTorch
- Apache-2.0
- auto-sklearn
- BSD-3-Clause
Last pushed
- Auto-PyTorch
- Apr 9, 2024
- auto-sklearn
- Jun 29, 2026
Categories
- Auto-PyTorch
- Data & Retrieval, Model Training
- auto-sklearn
- Model Training
Trust and health
Maintenance
- Auto-PyTorch
- Dormant (18%)
- auto-sklearn
- Steady (60%)
Days since push
- Auto-PyTorch
- 846d
- auto-sklearn
- 35d
Open issues (now)
- Auto-PyTorch
- 75
- auto-sklearn
- 209
Full report
- Auto-PyTorch
- Trust report
- auto-sklearn
- Trust report
Shared compatibility
- Python · Auto-PyTorch: Python runtime · auto-sklearn: Python runtime
Choose Auto-PyTorch if…
- License: Auto-PyTorch is Apache-2.0, auto-sklearn is BSD-3-Clause.
- Tags unique to Auto-PyTorch: deep-learning, pytorch, tabular-data, time-series-forecasting.
- Also covers Data & Retrieval.
- Use when you need to automate both architectural searches and hyperparameter tuning specifically for PyTorch-based deep learning models.
When NOT to use Auto-PyTorch
- Avoid using it if your AI development focuses on frameworks other than PyTorch.
- Do not use when the requirements do not involve deep learning models or you are not interested in automating architecture search and hyperparameter tuning.
Choose auto-sklearn if…
- License: auto-sklearn is BSD-3-Clause, Auto-PyTorch is Apache-2.0.
- Tags unique to auto-sklearn: automated-machine-learning, bayesian-optimization, hyperparameter-optimization, hyperparameter-search.
- When you need a drop-in replacement estimator for your existing scikit-learn pipeline that can handle the complexity of hyperparameter tuning automatically.
When NOT to use auto-sklearn
- If extensive customization or control over individual machine learning components is required beyond what auto-sklearn's automation offers.
- In cases requiring non-scikit-learn model ensembles, as the toolkit primarily supports models that are part of the scikit-earn library.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (automl/Auto-PyTorch) · observed Aug 4, 2026
- GitHub forks (automl/Auto-PyTorch) · observed Aug 4, 2026
- Last push (automl/Auto-PyTorch) · observed Apr 9, 2024
- License file (Apache-2.0) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (automl/auto-sklearn) · observed Aug 4, 2026
- GitHub forks (automl/auto-sklearn) · observed Aug 4, 2026
- Last push (automl/auto-sklearn) · observed Jun 29, 2026
- License file (BSD-3-Clause) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Auto-PyTorch 2.5k · auto-sklearn 8.1k (synced Aug 4, 2026).
Common questions
- What is the difference between Auto-PyTorch and auto-sklearn?
- Auto-PyTorch: Automatic architecture search and hyperparameter optimization for PyTorch. auto-sklearn: Automated Machine Learning with scikit-learn. See the comparison table for live GitHub stats and shared categories.
- When should I choose Auto-PyTorch over auto-sklearn?
- Choose Auto-PyTorch over auto-sklearn when License: Auto-PyTorch is Apache-2.0, auto-sklearn is BSD-3-Clause; Tags unique to Auto-PyTorch: deep-learning, pytorch, tabular-data, time-series-forecasting; Also covers Data & Retrieval; Use when you need to automate both architectural searches and hyperparameter tuning specifically for PyTorch-based deep learning models.
- When should I choose auto-sklearn over Auto-PyTorch?
- Choose auto-sklearn over Auto-PyTorch when License: auto-sklearn is BSD-3-Clause, Auto-PyTorch is Apache-2.0; Tags unique to auto-sklearn: automated-machine-learning, bayesian-optimization, hyperparameter-optimization, hyperparameter-search; When you need a drop-in replacement estimator for your existing scikit-learn pipeline that can handle the complexity of hyperparameter tuning automatically.
- When should I avoid Auto-PyTorch?
- Avoid using it if your AI development focuses on frameworks other than PyTorch. Do not use when the requirements do not involve deep learning models or you are not interested in automating architecture search and hyperparameter tuning.
- When should I avoid auto-sklearn?
- If extensive customization or control over individual machine learning components is required beyond what auto-sklearn's automation offers. In cases requiring non-scikit-learn model ensembles, as the toolkit primarily supports models that are part of the scikit-earn library.
- Is Auto-PyTorch or auto-sklearn more popular on GitHub?
- auto-sklearn has more GitHub stars (8,127 vs 2,541). Stars measure visibility, not whether either tool fits your constraints.
- Are Auto-PyTorch and auto-sklearn open source?
- Yes - both are open-source projects on GitHub (Auto-PyTorch: Apache-2.0, auto-sklearn: BSD-3-Clause).
- Where can I find alternatives to Auto-PyTorch or auto-sklearn?
- GraphCanon lists graph-backed alternatives at Auto-PyTorch alternatives and auto-sklearn alternatives (Auto-PyTorch markdown twin, auto-sklearn markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, Auto-PyTorch or auto-sklearn?
- Auto-PyTorch: Dormant. auto-sklearn: Steady. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
- Where are the full trust reports for Auto-PyTorch and auto-sklearn?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Auto-PyTorch trust report; auto-sklearn trust report.