Comparison
Auto-PyTorch vs katib
Verdict
Pick Auto-PyTorch if auto-PyTorch specializes in automatic architecture search and hyperparameter optimization for deep-learning models using PyTorch; pick katib if katib is an automated machine learning solution for Kubernetes environments, focused on hyperparameter tuning and neural architecture search.
Markdown twin · Auto-PyTorch alternatives · katib alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | Auto-PyTorch | katib |
|---|---|---|
| Maintenance | Dormant (846d since push) As of 2w · github_public_v1 | Very active (0d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 2w · 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
- katib
- Automated Machine Learning on Kubernetes
Stars
- Auto-PyTorch
- 2.5k
- katib
- 1.7k
Forks
- Auto-PyTorch
- 303
- katib
- 534
Open issues
- Auto-PyTorch
- 75
- katib
- 106
Language
- Auto-PyTorch
- Python
- katib
- Python
Adopt for
- Auto-PyTorch
- Auto-PyTorch specializes in automatic architecture search and hyperparameter optimization for deep-learning models using PyTorch.
- katib
- Katib is an automated machine learning solution for Kubernetes environments, focused on hyperparameter tuning and neural architecture search.
Persona
- Auto-PyTorch
- -
- katib
- -
Runtime
- Auto-PyTorch
- -
- katib
- -
License
- Auto-PyTorch
- Apache-2.0
- katib
- Apache-2.0
Last pushed
- Auto-PyTorch
- Apr 9, 2024
- katib
- Aug 4, 2026
Categories
- Auto-PyTorch
- Data & Retrieval, Model Training
- katib
- Evaluation & Observability, Model Training
Trust and health
Maintenance
- Auto-PyTorch
- Dormant (18%)
- katib
- Very active (96%)
Days since push
- Auto-PyTorch
- 846d
- katib
- 0d
Open issues (now)
- Auto-PyTorch
- 75
- katib
- 106
Full report
- Auto-PyTorch
- Trust report
- katib
- Trust report
Shared compatibility
- Python · Auto-PyTorch: Python runtime · katib: Python runtime
Choose Auto-PyTorch if…
- Tags unique to Auto-PyTorch: deep-learning, pytorch, tabular-data, time-series-forecasting.
- Also covers Data & Retrieval.
- Auto-PyTorch ships Docker support for self-hosted deployment.
- 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 katib if…
- Tags unique to katib: ai, hyperparameter-tuning, neural-architecture-search.
- Also covers Evaluation & Observability.
- When you need to perform comprehensive hyperparameter tuning tasks within a Kubernetes cluster setup.
When NOT to use katib
- Avoid using Katib if you do not have a Kubernetes cluster setup, as it heavily relies on this platform for operation.
- If your project's requirements do not extend beyond simple model training tasks and you lack the resources to support a complex CI/CD pipeline like Kubeflow with Katib.
- Not suitable when working in environments with strict constraints preventing the use of open-source tools under Apache-2.0 licenses.
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 (kubeflow/katib) · observed Aug 4, 2026
- GitHub forks (kubeflow/katib) · observed Aug 4, 2026
- Last push (kubeflow/katib) · observed Aug 4, 2026
- License file (Apache-2.0) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Auto-PyTorch 2.5k · katib 1.7k (synced Aug 4, 2026).
Common questions
- What is the difference between Auto-PyTorch and katib?
- Auto-PyTorch: Automatic architecture search and hyperparameter optimization for PyTorch. katib: Automated Machine Learning on Kubernetes. See the comparison table for live GitHub stats and shared categories.
- When should I choose Auto-PyTorch over katib?
- Choose Auto-PyTorch over katib when Tags unique to Auto-PyTorch: deep-learning, pytorch, tabular-data, time-series-forecasting; Also covers Data & Retrieval; Auto-PyTorch ships Docker support for self-hosted deployment; Use when you need to automate both architectural searches and hyperparameter tuning specifically for PyTorch-based deep learning models.
- When should I choose katib over Auto-PyTorch?
- Choose katib over Auto-PyTorch when Tags unique to katib: ai, hyperparameter-tuning, neural-architecture-search; Also covers Evaluation & Observability; When you need to perform comprehensive hyperparameter tuning tasks within a Kubernetes cluster setup.
- 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 katib?
- Avoid using Katib if you do not have a Kubernetes cluster setup, as it heavily relies on this platform for operation. If your project's requirements do not extend beyond simple model training tasks and you lack the resources to support a complex CI/CD pipeline like Kubeflow with Katib. Not suitable when working in environments with strict constraints preventing the use of open-source tools under Apache-2.0 licenses.
- Is Auto-PyTorch or katib more popular on GitHub?
- Auto-PyTorch has more GitHub stars (2,541 vs 1,694). Stars measure visibility, not whether either tool fits your constraints.
- Are Auto-PyTorch and katib open source?
- Yes - both are open-source projects on GitHub (Auto-PyTorch: Apache-2.0, katib: Apache-2.0).
- Where can I find alternatives to Auto-PyTorch or katib?
- GraphCanon lists graph-backed alternatives at Auto-PyTorch alternatives and katib alternatives (Auto-PyTorch markdown twin, katib 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 katib?
- Auto-PyTorch: Dormant. katib: Very active. 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 katib?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Auto-PyTorch trust report; katib trust report.