Comparison
awesome-evals vs awesome-ai-safety
Verdict
Pick awesome-evals if curated resources for AI agent evaluation with BenchFlow backing its maintenance; pick awesome-ai-safety if awesome-ai-safety is a curated list of papers and technical articles focused on ensuring AI quality and safety across various machine learning domains including CV and NLP.
Markdown twin · awesome-evals alternatives · awesome-ai-safety alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | awesome-evals | awesome-ai-safety |
|---|---|---|
| Maintenance | Active (26d since push) As of 3w · github_public_v1 | Dormant (473d 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 | 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
- awesome-evals
- A curated library of resources for building and evaluating AI agents
- awesome-ai-safety
- A curated list of papers and technical articles on AI Quality & Safety
Stars
- awesome-evals
- 761
- awesome-ai-safety
- 220
Forks
- awesome-evals
- 71
- awesome-ai-safety
- 39
Open issues
- awesome-evals
- 21
- awesome-ai-safety
- 17
Language
- awesome-evals
- -
- awesome-ai-safety
- -
Adopt for
- awesome-evals
- Curated resources for AI agent evaluation with BenchFlow backing its maintenance
- awesome-ai-safety
- awesome-ai-safety is a curated list of papers and technical articles focused on ensuring AI quality and safety across various machine learning domains including CV and NLP.
Persona
- awesome-evals
- -
- awesome-ai-safety
- -
Runtime
- awesome-evals
- -
- awesome-ai-safety
- -
License
- awesome-evals
- Other
- awesome-ai-safety
- Apache-2.0
Last pushed
- awesome-evals
- Jul 1, 2026
- awesome-ai-safety
- Apr 14, 2025
Categories
- awesome-evals
- AI Agents, Evaluation & Observability
- awesome-ai-safety
- Evaluation & Observability
Trust and health
Maintenance
- awesome-evals
- Active (82%)
- awesome-ai-safety
- Dormant (18%)
Days since push
- awesome-evals
- 26d
- awesome-ai-safety
- 473d
Open issues (now)
- awesome-evals
- 21
- awesome-ai-safety
- 17
Full report
- awesome-evals
- Trust report
- awesome-ai-safety
- Trust report
Choose awesome-evals if…
- License: awesome-evals is Other, awesome-ai-safety is Apache-2.0.
- Tags unique to awesome-evals: agent-evaluation, ai-agents, awesome-list, benchmarks.
- Also covers AI Agents.
- Need diverse resources encompassing papers, blogs, talks, tools, and benchmarks specifically curated for AI agent evaluation
When NOT to use awesome-evals
- Require real-time interactive support or direct tool integrations not covered by a static resource list
- Seeking proprietary tools from specific vendors rather than open resources and community content
Choose awesome-ai-safety if…
- License: awesome-ai-safety is Apache-2.0, awesome-evals is Other.
- Pricing: The repository is free to use under the Apache-2.0 license. However, external resources linked might have their own licensing terms or costs..
- Tags unique to awesome-ai-safety: ai, ai safety, ai-alignment, ai-quality.
- When you need an aggregated source to explore topics such as AI alignment, robustness, fairness in ML models.
When NOT to use awesome-ai-safety
- Not suitable if your requirement is a repository with hands-on coding examples rather than research papers and articles.
- Avoid this resource if you are searching for datasets or tools that are not in the form of academic literature but practical utilities.
- This platform may not provide sufficient guidance on hardware-specific testing, where practical constraints diverge from theoretical models.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (benchflow-ai/awesome-evals) · observed Jul 28, 2026
- GitHub forks (benchflow-ai/awesome-evals) · observed Jul 28, 2026
- Last push (benchflow-ai/awesome-evals) · observed Jul 1, 2026
- License file (Other) · observed Jul 28, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Giskard-AI/awesome-ai-safety) · observed Aug 1, 2026
- GitHub forks (Giskard-AI/awesome-ai-safety) · observed Aug 1, 2026
- Last push (Giskard-AI/awesome-ai-safety) · observed Apr 14, 2025
- License file (Apache-2.0) · observed Aug 1, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: awesome-evals 761 · awesome-ai-safety 220 (synced Jul 28, 2026).
Common questions
- What is the difference between awesome-evals and awesome-ai-safety?
- awesome-evals: A curated library of resources for building and evaluating AI agents. awesome-ai-safety: A curated list of papers and technical articles on AI Quality & Safety. See the comparison table for live GitHub stats and shared categories.
- When should I choose awesome-evals over awesome-ai-safety?
- Choose awesome-evals over awesome-ai-safety when License: awesome-evals is Other, awesome-ai-safety is Apache-2.0; Tags unique to awesome-evals: agent-evaluation, ai-agents, awesome-list, benchmarks; Also covers AI Agents; Need diverse resources encompassing papers, blogs, talks, tools, and benchmarks specifically curated for AI agent evaluation.
- When should I choose awesome-ai-safety over awesome-evals?
- Choose awesome-ai-safety over awesome-evals when License: awesome-ai-safety is Apache-2.0, awesome-evals is Other; Pricing: The repository is free to use under the Apache-2.0 license. However, external resources linked might have their own licensing terms or costs.; Tags unique to awesome-ai-safety: ai, ai safety, ai-alignment, ai-quality; When you need an aggregated source to explore topics such as AI alignment, robustness, fairness in ML models.
- When should I avoid awesome-evals?
- Require real-time interactive support or direct tool integrations not covered by a static resource list Seeking proprietary tools from specific vendors rather than open resources and community content
- When should I avoid awesome-ai-safety?
- Not suitable if your requirement is a repository with hands-on coding examples rather than research papers and articles. Avoid this resource if you are searching for datasets or tools that are not in the form of academic literature but practical utilities. This platform may not provide sufficient guidance on hardware-specific testing, where practical constraints diverge from theoretical models.
- Is awesome-evals or awesome-ai-safety more popular on GitHub?
- awesome-evals has more GitHub stars (761 vs 220). Stars measure visibility, not whether either tool fits your constraints.
- Are awesome-evals and awesome-ai-safety open source?
- Yes - both are open-source projects on GitHub (awesome-evals: Other, awesome-ai-safety: Apache-2.0).
- Where can I find alternatives to awesome-evals or awesome-ai-safety?
- GraphCanon lists graph-backed alternatives at awesome-evals alternatives and awesome-ai-safety alternatives (awesome-evals markdown twin, awesome-ai-safety 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, awesome-evals or awesome-ai-safety?
- awesome-evals: Active. awesome-ai-safety: 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 awesome-evals and awesome-ai-safety?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome-evals trust report; awesome-ai-safety trust report.