Comparison
Spearmint vs awesome-AutoML
Verdict
Pick Spearmint if a specialized package for performing Bayesian optimization, Spearmint automates experiment running and parameter tuning to minimize objectives efficiently; pick awesome-AutoML if curates AutoML research across neural architecture search, hyperparameter optimization, and meta-learning.
Markdown twin · Spearmint alternatives · awesome-AutoML alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | Spearmint | awesome-AutoML |
|---|---|---|
| Maintenance | Dormant (2411d since push) As of 3w · github_public_v1 | Slowing (133d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Personal account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) 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
- Spearmint
- Bayesian optimization codebase
- awesome-AutoML
- Curating AutoML research and resources
Stars
- Spearmint
- 1.6k
- awesome-AutoML
- 941
Forks
- Spearmint
- 327
- awesome-AutoML
- 156
Open issues
- Spearmint
- 77
- awesome-AutoML
- 1
Language
- Spearmint
- Python
- awesome-AutoML
- -
Adopt for
- Spearmint
- A specialized package for performing Bayesian optimization, Spearmint automates experiment running and parameter tuning to minimize objectives efficiently.
- awesome-AutoML
- Curates AutoML research across neural architecture search, hyperparameter optimization, and meta-learning.
Persona
- Spearmint
- -
- awesome-AutoML
- -
Runtime
- Spearmint
- -
- awesome-AutoML
- -
License
- Spearmint
- Other
- awesome-AutoML
- GPL-3.0
Last pushed
- Spearmint
- Dec 27, 2019
- awesome-AutoML
- Mar 24, 2026
Categories
- Spearmint
- Model Training
- awesome-AutoML
- Model Training
Trust and health
Maintenance
- Spearmint
- Dormant (18%)
- awesome-AutoML
- Slowing (36%)
Days since push
- Spearmint
- 2411d
- awesome-AutoML
- 133d
Open issues (now)
- Spearmint
- 77
- awesome-AutoML
- 1
Owner type
- Spearmint
- Organization
- awesome-AutoML
- User
Full report
- Spearmint
- Trust report
- awesome-AutoML
- Trust report
Choose Spearmint if…
- License: Spearmint is Other, awesome-AutoML is GPL-3.0.
- 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
Choose awesome-AutoML if…
- License: awesome-AutoML is GPL-3.0, Spearmint is Other.
- Tags unique to awesome-AutoML: automl, hyperparameter-optimization, meta-learning, neural-architecture-search.
- When seeking comprehensive resources on diverse AutoML topics from recent and impactful research.
When NOT to use awesome-AutoML
- If looking for direct implementation advice as the repository focuses more on linking to resources rather than providing specific how-to guides.
- When requiring real-time or interactive AutoML features, since it's a curation hub rather than an application tool.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- 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 (windmaple/awesome-AutoML) · observed Aug 4, 2026
- GitHub forks (windmaple/awesome-AutoML) · observed Aug 4, 2026
- Last push (windmaple/awesome-AutoML) · observed Mar 24, 2026
- License file (GPL-3.0) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Spearmint 1.6k · awesome-AutoML 941 (synced Aug 4, 2026).
Common questions
- What is the difference between Spearmint and awesome-AutoML?
- Spearmint: Bayesian optimization codebase. awesome-AutoML: Curating AutoML research and resources. See the comparison table for live GitHub stats and shared categories.
- When should I choose Spearmint over awesome-AutoML?
- Choose Spearmint over awesome-AutoML when License: Spearmint is Other, awesome-AutoML is GPL-3.0; 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 choose awesome-AutoML over Spearmint?
- Choose awesome-AutoML over Spearmint when License: awesome-AutoML is GPL-3.0, Spearmint is Other; Tags unique to awesome-AutoML: automl, hyperparameter-optimization, meta-learning, neural-architecture-search; When seeking comprehensive resources on diverse AutoML topics from recent and impactful research.
- 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
- When should I avoid awesome-AutoML?
- If looking for direct implementation advice as the repository focuses more on linking to resources rather than providing specific how-to guides. When requiring real-time or interactive AutoML features, since it's a curation hub rather than an application tool.
- Is Spearmint or awesome-AutoML more popular on GitHub?
- Spearmint has more GitHub stars (1,573 vs 941). Stars measure visibility, not whether either tool fits your constraints.
- Are Spearmint and awesome-AutoML open source?
- Yes - both are open-source projects on GitHub (Spearmint: Other, awesome-AutoML: GPL-3.0).
- Where can I find alternatives to Spearmint or awesome-AutoML?
- GraphCanon lists graph-backed alternatives at Spearmint alternatives and awesome-AutoML alternatives (Spearmint markdown twin, awesome-AutoML 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, Spearmint or awesome-AutoML?
- Spearmint: Dormant. awesome-AutoML: Slowing. 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 Spearmint and awesome-AutoML?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Spearmint trust report; awesome-AutoML trust report.