Comparison
athina-evals vs every_eval_ever
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 every_eval_ever if every Eval Ever is dedicated to providing a standardized metadata framework and a crowdsourced evaluation database for AI results.
Markdown twin · athina-evals alternatives · every_eval_ever alternatives
GraphCanon updated Sep 20, 2026
16views this month
Trust & integrity
| Signal | athina-evals | every_eval_ever |
|---|---|---|
| Maintenance | Dormant (470d since push) As of Sep 20, 2026 · github_public_v1 | Very active (1d since push) As of Sep 9, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 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
- athina-evals
- Python SDK for evaluating LLM generated responses
- every_eval_ever
- Shared schema and crowdsourced eval database
Stars
- athina-evals
- 301
- every_eval_ever
- 111
Forks
- athina-evals
- 22
- every_eval_ever
- 49
Open issues
- athina-evals
- 4
- every_eval_ever
- 27
Language
- athina-evals
- Python
- every_eval_ever
- 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.
- every_eval_ever
- Every Eval Ever is dedicated to providing a standardized metadata framework and a crowdsourced evaluation database for AI results.
Persona
- athina-evals
- -
- every_eval_ever
- -
Runtime
- athina-evals
- -
- every_eval_ever
- -
License
- athina-evals
- -
- every_eval_ever
- MIT
Last pushed
- athina-evals
- Jun 6, 2025
- every_eval_ever
- Sep 7, 2026
Categories
- athina-evals
- Evaluation & Observability
- every_eval_ever
- Evaluation & Observability
Trust and health
Maintenance
- athina-evals
- Dormant (18%)
- every_eval_ever
- Very active (96%)
Days since push
- athina-evals
- 470d
- every_eval_ever
- 1d
Open issues (now)
- athina-evals
- 4
- every_eval_ever
- 27
Stars delta
- athina-evals
- 0 (30d)
- every_eval_ever
- +9 (30d)
Open issues delta
- athina-evals
- +1 (30d)
- every_eval_ever
- +3 (30d)
Full report
- athina-evals
- Trust report
- every_eval_ever
- 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 111) - 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 every_eval_ever if…
- Pricing: Every Eval Ever is open-source under the MIT license, allowing free use and modification. No direct costs are associated with using the schema or contributing to the database..
- Requirements: Min 2 GB RAM; To utilize all features, you need to install specific converter dependencies via pip..
- Tags unique to every_eval_ever: agent-evaluation, ai-evaluation, evaluations, infra.
- Use Every Eval Ever if you need to compare evaluation results from different frameworks in a consistent manner, ensuring results can be easily reproduced or reused as they conform to a defined schema.
When NOT to use every_eval_ever
- Avoid Every Eval Ever if you require real-time updates on evaluation results, as the database relies on contributions from a community to maintain and update its dataset.
- If your project needs to integrate evaluation outcomes without an explicit need for extensive metadata validation or standardization, this tool might be less suitable.
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 Sep 20, 2026
- GitHub forks (athina-ai/athina-evals) · observed Sep 20, 2026
- Last push (athina-ai/athina-evals) · observed Jun 6, 2025
- License file (unknown) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (evaleval/every_eval_ever) · observed Sep 20, 2026
- GitHub forks (evaleval/every_eval_ever) · observed Sep 20, 2026
- Last push (evaleval/every_eval_ever) · observed Sep 7, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: athina-evals 301 · every_eval_ever 111 (synced Sep 20, 2026).
Common questions
- What is the difference between athina-evals and every_eval_ever?
- athina-evals: Python SDK for evaluating LLM generated responses. every_eval_ever: Shared schema and crowdsourced eval database. See the comparison table for live GitHub stats and shared categories.
- When should I choose athina-evals over every_eval_ever?
- Choose athina-evals over every_eval_ever 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 111) - visibility, not fit.
- When should I choose every_eval_ever over athina-evals?
- Choose every_eval_ever over athina-evals when Pricing: Every Eval Ever is open-source under the MIT license, allowing free use and modification. No direct costs are associated with using the schema or contributing to the database.; Requirements: Min 2 GB RAM; To utilize all features, you need to install specific converter dependencies via pip.; Tags unique to every_eval_ever: agent-evaluation, ai-evaluation, evaluations, infra; Use Every Eval Ever if you need to compare evaluation results from different frameworks in a consistent manner, ensuring results can be easily reproduced or reused as they conform to a defined schema.
- 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 every_eval_ever?
- Avoid Every Eval Ever if you require real-time updates on evaluation results, as the database relies on contributions from a community to maintain and update its dataset. If your project needs to integrate evaluation outcomes without an explicit need for extensive metadata validation or standardization, this tool might be less suitable.
- Is athina-evals or every_eval_ever more popular on GitHub?
- athina-evals has more GitHub stars (301 vs 111). Stars measure visibility, not whether either tool fits your constraints.
- Are athina-evals and every_eval_ever open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to athina-evals or every_eval_ever?
- GraphCanon lists graph-backed alternatives at athina-evals alternatives and every_eval_ever alternatives (athina-evals markdown twin, every_eval_ever 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 every_eval_ever?
- athina-evals: Dormant. every_eval_ever: Very active. 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 every_eval_ever?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: athina-evals trust report; every_eval_ever trust report.