Comparison
Spearmint vs awesome-mlops
Verdict
Pick Spearmint if a specialized package for performing Bayesian optimization, Spearmint automates experiment running and parameter tuning to minimize objectives efficiently; pick awesome-mlops if awesome-mlops curates MLOps resources focusing on diverse deployment strategies and tooling.
Markdown twin · Spearmint alternatives · awesome-mlops alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | Spearmint | awesome-mlops |
|---|---|---|
| Maintenance | Dormant (2411d since push) As of 3w · github_public_v1 | Dormant (621d 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-mlops
- A curated list of references for MLOps
Stars
- Spearmint
- 1.6k
- awesome-mlops
- 14k
Forks
- Spearmint
- 327
- awesome-mlops
- 2.1k
Open issues
- Spearmint
- 77
- awesome-mlops
- 44
Language
- Spearmint
- Python
- awesome-mlops
- -
Adopt for
- Spearmint
- A specialized package for performing Bayesian optimization, Spearmint automates experiment running and parameter tuning to minimize objectives efficiently.
- awesome-mlops
- awesome-mlops curates MLOps resources focusing on diverse deployment strategies and tooling.
Persona
- Spearmint
- -
- awesome-mlops
- -
Runtime
- Spearmint
- -
- awesome-mlops
- -
License
- Spearmint
- Other
- awesome-mlops
- -
Last pushed
- Spearmint
- Dec 27, 2019
- awesome-mlops
- Nov 21, 2024
Categories
- Spearmint
- Model Training
- awesome-mlops
- Inference & Serving, Model Training
Trust and health
Days since push
- Spearmint
- 2411d
- awesome-mlops
- 621d
Open issues (now)
- Spearmint
- 77
- awesome-mlops
- 44
Owner type
- Spearmint
- Organization
- awesome-mlops
- User
Full report
- Spearmint
- Trust report
- awesome-mlops
- Trust report
Shared compatibility
- Python · Spearmint: Python runtime · awesome-mlops: Python runtime
Choose Spearmint if…
- 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-mlops if…
- Tags unique to awesome-mlops: ai, data-science, devops, engineering.
- Also covers Inference & Serving.
- If you need references covering online training and inference service architecture patterns, consider awesome-mlops.
When NOT to use awesome-mlops
- Avoid if focused solely on a single MLOps tool or framework as this is a broad resource list.
- Not suitable for those seeking end-to-end support beyond references, like hands-on deployment assistance.
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 (visenger/awesome-mlops) · observed Aug 4, 2026
- GitHub forks (visenger/awesome-mlops) · observed Aug 4, 2026
- Last push (visenger/awesome-mlops) · observed Nov 21, 2024
- License file (unknown) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: Spearmint 1.6k · awesome-mlops 14k (synced Aug 4, 2026).
Common questions
- What is the difference between Spearmint and awesome-mlops?
- Spearmint: Bayesian optimization codebase. awesome-mlops: A curated list of references for MLOps. See the comparison table for live GitHub stats and shared categories.
- When should I choose Spearmint over awesome-mlops?
- Choose Spearmint over awesome-mlops when 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-mlops over Spearmint?
- Choose awesome-mlops over Spearmint when Tags unique to awesome-mlops: ai, data-science, devops, engineering; Also covers Inference & Serving; If you need references covering online training and inference service architecture patterns, consider awesome-mlops.
- 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-mlops?
- Avoid if focused solely on a single MLOps tool or framework as this is a broad resource list. Not suitable for those seeking end-to-end support beyond references, like hands-on deployment assistance.
- Is Spearmint or awesome-mlops more popular on GitHub?
- awesome-mlops has more GitHub stars (14,127 vs 1,573). Stars measure visibility, not whether either tool fits your constraints.
- Are Spearmint and awesome-mlops open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to Spearmint or awesome-mlops?
- GraphCanon lists graph-backed alternatives at Spearmint alternatives and awesome-mlops alternatives (Spearmint markdown twin, awesome-mlops 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-mlops?
- Spearmint: Dormant. awesome-mlops: 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 Spearmint and awesome-mlops?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Spearmint trust report; awesome-mlops trust report.