Comparison
Auto-PyTorch vs Spearmint
Verdict
Pick Auto-PyTorch if auto-PyTorch specializes in automatic architecture search and hyperparameter optimization for deep-learning models using PyTorch; pick Spearmint if a specialized package for performing Bayesian optimization, Spearmint automates experiment running and parameter tuning to minimize objectives efficiently.
Markdown twin · Auto-PyTorch alternatives · Spearmint alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | Auto-PyTorch | Spearmint |
|---|---|---|
| Maintenance | Dormant (846d since push) As of 3w · github_public_v1 | Dormant (2411d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | No lockfile (source not queried) 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
- Spearmint
- Bayesian optimization codebase
Stars
- Auto-PyTorch
- 2.5k
- Spearmint
- 1.6k
Forks
- Auto-PyTorch
- 303
- Spearmint
- 327
Open issues
- Auto-PyTorch
- 75
- Spearmint
- 77
Language
- Auto-PyTorch
- Python
- Spearmint
- Python
Adopt for
- Auto-PyTorch
- Auto-PyTorch specializes in automatic architecture search and hyperparameter optimization for deep-learning models using PyTorch.
- Spearmint
- A specialized package for performing Bayesian optimization, Spearmint automates experiment running and parameter tuning to minimize objectives efficiently.
Persona
- Auto-PyTorch
- -
- Spearmint
- -
Runtime
- Auto-PyTorch
- -
- Spearmint
- -
License
- Auto-PyTorch
- Apache-2.0
- Spearmint
- Other
Last pushed
- Auto-PyTorch
- Apr 9, 2024
- Spearmint
- Dec 27, 2019
Categories
- Auto-PyTorch
- Data & Retrieval, Model Training
- Spearmint
- Model Training
Trust and health
Days since push
- Auto-PyTorch
- 846d
- Spearmint
- 2411d
Open issues (now)
- Auto-PyTorch
- 75
- Spearmint
- 77
OSV dependency advisories
- Auto-PyTorch
- Published findings
- Spearmint
- No lockfile (source not queried)
Full report
- Auto-PyTorch
- Trust report
- Spearmint
- Trust report
Shared compatibility
- Python · Auto-PyTorch: Python runtime · Spearmint: Python runtime
Choose Auto-PyTorch if…
- License: Auto-PyTorch is Apache-2.0, Spearmint is Other.
- Tags unique to Auto-PyTorch: automl, deep-learning, pytorch, tabular-data.
- 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 Spearmint if…
- License: Spearmint is Other, Auto-PyTorch is Apache-2.0.
- Tags unique to Spearmint: automated-experimentation, bayesian-optimization, hyperparameter-tuning.
- - When you require automated experimentation with parameters that can be iteratively adjusted
When NOT to use Spearmint
- - If your project requires a permissive license as Spearmint operates under an Academic and Non-Commercial Research Use License
- - If you need real-time or continuous parameter tuning outside of batch experimentation contexts as Spearmint is suited for controlled experiment setups
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 (HIPS/Spearmint) · observed Aug 4, 2026
- GitHub forks (HIPS/Spearmint) · observed Aug 4, 2026
- Last push (HIPS/Spearmint) · observed Dec 27, 2019
- License file (Other) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Auto-PyTorch 2.5k · Spearmint 1.6k (synced Aug 4, 2026).
Common questions
- What is the difference between Auto-PyTorch and Spearmint?
- Auto-PyTorch: Automatic architecture search and hyperparameter optimization for PyTorch. Spearmint: Bayesian optimization codebase. See the comparison table for live GitHub stats and shared categories.
- When should I choose Auto-PyTorch over Spearmint?
- Choose Auto-PyTorch over Spearmint when License: Auto-PyTorch is Apache-2.0, Spearmint is Other; Tags unique to Auto-PyTorch: automl, deep-learning, pytorch, tabular-data; 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 Spearmint over Auto-PyTorch?
- Choose Spearmint over Auto-PyTorch when License: Spearmint is Other, Auto-PyTorch is Apache-2.0; Tags unique to Spearmint: automated-experimentation, bayesian-optimization, hyperparameter-tuning; - When you require automated experimentation with parameters that can be iteratively adjusted.
- 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 Spearmint?
- - If your project requires a permissive license as Spearmint operates under an Academic and Non-Commercial Research Use License - If you need real-time or continuous parameter tuning outside of batch experimentation contexts as Spearmint is suited for controlled experiment setups
- Is Auto-PyTorch or Spearmint more popular on GitHub?
- Auto-PyTorch has more GitHub stars (2,541 vs 1,573). Stars measure visibility, not whether either tool fits your constraints.
- Are Auto-PyTorch and Spearmint open source?
- Yes - both are open-source projects on GitHub (Auto-PyTorch: Apache-2.0, Spearmint: Other).
- Where can I find alternatives to Auto-PyTorch or Spearmint?
- GraphCanon lists graph-backed alternatives at Auto-PyTorch alternatives and Spearmint alternatives (Auto-PyTorch markdown twin, Spearmint 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 Spearmint?
- Auto-PyTorch: Dormant. Spearmint: Dormant. 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 Spearmint?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Auto-PyTorch trust report; Spearmint trust report.