Comparison
athina-evals vs jailbreak-evaluation
Verdict
Pick athina-evals if athina-evals is a Python SDK developed for facilitating the evaluation of outputs from large language models through predefined metrics and frameworks; pick jailbreak-evaluation if jailbreak-evaluation is a Python package aimed at evaluating if AI models have been jailbroken by generating outputs that diverge from expected programming.
Markdown twin · athina-evals alternatives · jailbreak-evaluation alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | athina-evals | jailbreak-evaluation |
|---|---|---|
| Maintenance | Dormant (417d since push) As of 3w · github_public_v1 | Dormant (638d 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 | 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
- athina-evals
- Python SDK for evaluating LLM generated responses
- jailbreak-evaluation
- Python package for language model jailbreak evaluation
Stars
- athina-evals
- 301
- jailbreak-evaluation
- 27
Forks
- athina-evals
- 22
- jailbreak-evaluation
- 8
Open issues
- athina-evals
- 3
- jailbreak-evaluation
- 0
Language
- athina-evals
- Python
- jailbreak-evaluation
- Python
Adopt for
- athina-evals
- athina-evals is a Python SDK developed for facilitating the evaluation of outputs from large language models through predefined metrics and frameworks.
- jailbreak-evaluation
- jailbreak-evaluation is a Python package aimed at evaluating if AI models have been jailbroken by generating outputs that diverge from expected programming.
Persona
- athina-evals
- -
- jailbreak-evaluation
- -
Runtime
- athina-evals
- -
- jailbreak-evaluation
- -
License
- athina-evals
- -
- jailbreak-evaluation
- Apache-2.0
Last pushed
- athina-evals
- Jun 6, 2025
- jailbreak-evaluation
- Nov 4, 2024
Categories
- athina-evals
- Evaluation & Observability
- jailbreak-evaluation
- Evaluation & Observability
Trust and health
Days since push
- athina-evals
- 417d
- jailbreak-evaluation
- 638d
Open issues (now)
- athina-evals
- 3
- jailbreak-evaluation
- 0
Full report
- athina-evals
- Trust report
- jailbreak-evaluation
- Trust report
Choose athina-evals if…
- Tags unique to athina-evals: evaluation, evaluation-framework, evaluation-metrics, llm-eval.
- When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics
- More GitHub stars (301 vs 27) - visibility, not fit.
When NOT to use athina-evals
- If open-source alternatives with transparent customization options are preferred over athina-evals' approach
- In scenarios where API access requirements limit the ability to perform evaluations offline or in private environments
Choose jailbreak-evaluation if…
- Requirements: The tool depends on having PyTorch and FastChat installed; An API key from the OpenAI Platform is required for full functionality.
- Tags unique to jailbreak-evaluation: ai safety, evaluation tools, jailbreaks, language-models.
- When you need to assess whether an AI model can be manipulated to produce unpredictable or unintended outcomes through specific inputs, such as jailbreaking.
When NOT to use jailbreak-evaluation
- If your project does not involve assessing the security or integrity of how an AI model responds to manipulative input techniques designed to exploit design weaknesses.
- When you do not need dependencies on specific frameworks like PyTorch and FastChat, as jailbreak-evaluation requires these without automating their installation.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (athina-ai/athina-evals) · observed Jul 28, 2026
- GitHub forks (athina-ai/athina-evals) · observed Jul 28, 2026
- Last push (athina-ai/athina-evals) · observed Jun 6, 2025
- License file (unknown) · observed Jul 28, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (controllability/jailbreak-evaluation) · observed Aug 5, 2026
- GitHub forks (controllability/jailbreak-evaluation) · observed Aug 5, 2026
- Last push (controllability/jailbreak-evaluation) · observed Nov 4, 2024
- License file (Apache-2.0) · observed Aug 5, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: athina-evals 301 · jailbreak-evaluation 27 (synced Jul 28, 2026).
Common questions
- What is the difference between athina-evals and jailbreak-evaluation?
- athina-evals: Python SDK for evaluating LLM generated responses. jailbreak-evaluation: Python package for language model jailbreak evaluation. See the comparison table for live GitHub stats and shared categories.
- When should I choose athina-evals over jailbreak-evaluation?
- Choose athina-evals over jailbreak-evaluation when Tags unique to athina-evals: evaluation, evaluation-framework, evaluation-metrics, llm-eval; When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics; More GitHub stars (301 vs 27) - visibility, not fit.
- When should I choose jailbreak-evaluation over athina-evals?
- Choose jailbreak-evaluation over athina-evals when Requirements: The tool depends on having PyTorch and FastChat installed; An API key from the OpenAI Platform is required for full functionality; Tags unique to jailbreak-evaluation: ai safety, evaluation tools, jailbreaks, language-models; When you need to assess whether an AI model can be manipulated to produce unpredictable or unintended outcomes through specific inputs, such as jailbreaking.
- When should I avoid athina-evals?
- If open-source alternatives with transparent customization options are preferred over athina-evals' approach In scenarios where API access requirements limit the ability to perform evaluations offline or in private environments
- When should I avoid jailbreak-evaluation?
- If your project does not involve assessing the security or integrity of how an AI model responds to manipulative input techniques designed to exploit design weaknesses. When you do not need dependencies on specific frameworks like PyTorch and FastChat, as jailbreak-evaluation requires these without automating their installation.
- Is athina-evals or jailbreak-evaluation more popular on GitHub?
- athina-evals has more GitHub stars (301 vs 27). Stars measure visibility, not whether either tool fits your constraints.
- Are athina-evals and jailbreak-evaluation open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to athina-evals or jailbreak-evaluation?
- GraphCanon lists graph-backed alternatives at athina-evals alternatives and jailbreak-evaluation alternatives (athina-evals markdown twin, jailbreak-evaluation 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, athina-evals or jailbreak-evaluation?
- athina-evals: Dormant. jailbreak-evaluation: 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 athina-evals and jailbreak-evaluation?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: athina-evals trust report; jailbreak-evaluation trust report.