Comparison
langfair vs circle-guard-bench
Verdict
Pick langfair if langFair is a Python library designed for assessing bias and fairness in large language model (LLM) use cases using user-specific prompts; pick circle-guard-bench if circle-guard-bench is a Python-based AI benchmark tool for evaluating large language model guard systems under various protection scenarios.
Markdown twin · langfair alternatives · circle-guard-bench alternatives
GraphCanon updated Sep 20, 2026
5views this month
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Trust & integrity
| Signal | langfair | circle-guard-bench |
|---|---|---|
| Maintenance | Active (12d since push) As of Sep 8, 2026 · github_public_v1 | Slowing (185d since push) As of Sep 9, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 8, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 9, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 2026 · 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
- langfair
- LangFair: Use-Case Level LLM Bias and Fairness Assessments
- circle-guard-bench
- AI benchmark for evaluating LLM guard systems
Stars
- langfair
- 261
- circle-guard-bench
- 75
Forks
- langfair
- 46
- circle-guard-bench
- 5
Open issues
- langfair
- 28
- circle-guard-bench
- 1
Language
- langfair
- Python
- circle-guard-bench
- Python
Adopt for
- langfair
- LangFair is a Python library designed for assessing bias and fairness in large language model (LLM) use cases using user-specific prompts.
- circle-guard-bench
- circle-guard-bench is a Python-based AI benchmark tool for evaluating large language model guard systems under various protection scenarios.
Persona
- langfair
- -
- circle-guard-bench
- -
Runtime
- langfair
- -
- circle-guard-bench
- -
License
- langfair
- Other
- circle-guard-bench
- Apache-2.0
Last pushed
- langfair
- Aug 26, 2026
- circle-guard-bench
- Mar 7, 2026
Categories
- langfair
- Evaluation & Observability
- circle-guard-bench
- Evaluation & Observability
Trust and health
Maintenance
- langfair
- Active (82%)
- circle-guard-bench
- Slowing (36%)
Days since push
- langfair
- 12d
- circle-guard-bench
- 185d
Open issues (now)
- langfair
- 28
- circle-guard-bench
- 1
Stars delta
- langfair
- 0 (30d)
- circle-guard-bench
- +3 (30d)
Open issues delta
- langfair
- +3 (30d)
- circle-guard-bench
- +1 (30d)
Full report
- langfair
- Trust report
- circle-guard-bench
- Trust report
Shared compatibility
- Python · langfair: Python runtime · circle-guard-bench: Python runtime
Choose langfair if…
- License: langfair is Other, circle-guard-bench is Apache-2.0.
- Tags unique to langfair: ai-safety, bias-detection, ethical ai, fairness-ml.
- - You need to conduct bias and fairness assessments specific to the application domain of your LLM.
When NOT to use langfair
- - If you require access to internal model states for your evaluations, as LangFair focuses on output-based metrics instead.
- - You are looking for a static benchmark assessment that does not consider use-case-specific prompts, preferring generalized metrics over tailored evaluations.
Choose circle-guard-bench if…
- License: circle-guard-bench is Apache-2.0, langfair is Other.
- Tags unique to circle-guard-bench: ai, benchmarking, guardrail, large-language-models.
- Use circle-guard-bench when you need to evaluate the effectiveness of guardrails and safeguards in your LLM environment, as it offers an unparalleled set of scenarios specific to these protections.
When NOT to use circle-guard-bench
- Avoid circle-guard-bench if your primary focus is on benchmarking the performance aspects like speed and latency of LLMs, as it specializes in evaluating protections rather than performance.
- Do not use this tool when you intend to conduct general purpose evaluations or comparisons between different LLM models that do not specifically involve security-related guard systems.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (cvs-health/langfair) · observed Sep 20, 2026
- GitHub forks (cvs-health/langfair) · observed Sep 20, 2026
- Last push (cvs-health/langfair) · observed Aug 26, 2026
- License file (Other) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (whitecircle/circle-guard-bench) · observed Sep 20, 2026
- GitHub forks (whitecircle/circle-guard-bench) · observed Sep 20, 2026
- Last push (whitecircle/circle-guard-bench) · observed Mar 7, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: langfair 261 · circle-guard-bench 75 (synced Sep 20, 2026).
Common questions
- What is the difference between langfair and circle-guard-bench?
- langfair: LangFair: Use-Case Level LLM Bias and Fairness Assessments. circle-guard-bench: AI benchmark for evaluating LLM guard systems. See the comparison table for live GitHub stats and shared categories.
- When should I choose langfair over circle-guard-bench?
- Choose langfair over circle-guard-bench when License: langfair is Other, circle-guard-bench is Apache-2.0; Tags unique to langfair: ai-safety, bias-detection, ethical ai, fairness-ml; - You need to conduct bias and fairness assessments specific to the application domain of your LLM.
- When should I choose circle-guard-bench over langfair?
- Choose circle-guard-bench over langfair when License: circle-guard-bench is Apache-2.0, langfair is Other; Tags unique to circle-guard-bench: ai, benchmarking, guardrail, large-language-models; Use circle-guard-bench when you need to evaluate the effectiveness of guardrails and safeguards in your LLM environment, as it offers an unparalleled set of scenarios specific to these protections.
- When should I avoid langfair?
- - If you require access to internal model states for your evaluations, as LangFair focuses on output-based metrics instead. - You are looking for a static benchmark assessment that does not consider use-case-specific prompts, preferring generalized metrics over tailored evaluations.
- When should I avoid circle-guard-bench?
- Avoid circle-guard-bench if your primary focus is on benchmarking the performance aspects like speed and latency of LLMs, as it specializes in evaluating protections rather than performance. Do not use this tool when you intend to conduct general purpose evaluations or comparisons between different LLM models that do not specifically involve security-related guard systems.
- Is langfair or circle-guard-bench more popular on GitHub?
- langfair has more GitHub stars (261 vs 75). Stars measure visibility, not whether either tool fits your constraints.
- Are langfair and circle-guard-bench open source?
- Yes - both are open-source projects on GitHub (langfair: Other, circle-guard-bench: Apache-2.0).
- Where can I find alternatives to langfair or circle-guard-bench?
- GraphCanon lists graph-backed alternatives at langfair alternatives and circle-guard-bench alternatives (langfair markdown twin, circle-guard-bench 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, langfair or circle-guard-bench?
- langfair: Active. circle-guard-bench: 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 langfair and circle-guard-bench?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: langfair trust report; circle-guard-bench trust report.