Comparison
athina-evals vs evals
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 evals if evals is an evaluation framework from OpenAI for assessing large language models and systems built with them. It includes an open-source registry of benchmarks and tools to create custom evaluations.
Markdown twin · athina-evals alternatives · evals alternatives
GraphCanon updated 2w
vs
Trust & integrity
| Signal | athina-evals | evals |
|---|---|---|
| Maintenance | Dormant (417d since push) As of 4w · github_public_v1 | Slowing (115d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 4w · 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
- evals
- Framework for evaluating LLMs and LLM systems with an open-source registry of benchmarks.
Stars
- athina-evals
- 301
- evals
- 19k
Forks
- athina-evals
- 22
- evals
- 3.0k
Open issues
- athina-evals
- 3
- evals
- 213
Language
- athina-evals
- Python
- evals
- 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.
- evals
- Evals is an evaluation framework from OpenAI for assessing large language models and systems built with them. It includes an open-source registry of benchmarks and tools to create custom evaluations.
Persona
- athina-evals
- -
- evals
- -
Runtime
- athina-evals
- -
- evals
- -
License
- athina-evals
- -
- evals
- Other
Last pushed
- athina-evals
- Jun 6, 2025
- evals
- Apr 14, 2026
Categories
- athina-evals
- Evaluation & Observability
- evals
- Evaluation & Observability
Trust and health
Maintenance
- athina-evals
- Dormant (18%)
- evals
- Slowing (36%)
Days since push
- athina-evals
- 417d
- evals
- 115d
Open issues (now)
- athina-evals
- 3
- evals
- 213
Full report
- athina-evals
- Trust report
- evals
- Trust report
Choose athina-evals if…
- Tags unique to athina-evals: evaluation, evaluation-metrics, llm-eval, llm-evaluation.
- When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics
- Leaner open-issue backlog (3).
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 evals if…
- Tags unique to evals: benchmarking, custom eval creation, large language models, llm systems.
- * When you need a comprehensive set of pre-existing evals and the ability to create your own tailored tests using specific use cases, especially within the OpenAI model ecosystem.
- More GitHub stars (19k vs 301) - visibility, not fit.
When NOT to use evals
- * When evaluating models or systems that do not benefit from being integrated with the OpenAI API, as some features like direct evals configuration in the OpenAI Dashboard require an OpenAI key.
- * If you are looking for an evaluation framework that doesn’t involve external dependencies such as Git Large File Storage (LFS) and specific Python version requirements (Python 3.9 minimum), or if a
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 (openai/evals) · observed Aug 7, 2026
- GitHub forks (openai/evals) · observed Aug 7, 2026
- Last push (openai/evals) · observed Apr 14, 2026
- License file (Other) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: athina-evals 301 · evals 19k (synced Jul 28, 2026).
Common questions
- What is the difference between athina-evals and evals?
- athina-evals: Python SDK for evaluating LLM generated responses. evals: Framework for evaluating LLMs and LLM systems with an open-source registry of benchmarks.. See the comparison table for live GitHub stats and shared categories.
- When should I choose athina-evals over evals?
- Choose athina-evals over evals when Tags unique to athina-evals: evaluation, evaluation-metrics, llm-eval, llm-evaluation; When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics; Leaner open-issue backlog (3).
- When should I choose evals over athina-evals?
- Choose evals over athina-evals when Tags unique to evals: benchmarking, custom eval creation, large language models, llm systems; * When you need a comprehensive set of pre-existing evals and the ability to create your own tailored tests using specific use cases, especially within the OpenAI model ecosystem; More GitHub stars (19k vs 301) - visibility, not fit.
- 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 evals?
- * When evaluating models or systems that do not benefit from being integrated with the OpenAI API, as some features like direct evals configuration in the OpenAI Dashboard require an OpenAI key. * If you are looking for an evaluation framework that doesn’t involve external dependencies such as Git Large File Storage (LFS) and specific Python version requirements (Python 3.9 minimum), or if a
- Is athina-evals or evals more popular on GitHub?
- evals has more GitHub stars (19,127 vs 301). Stars measure visibility, not whether either tool fits your constraints.
- Are athina-evals and evals open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to athina-evals or evals?
- GraphCanon lists graph-backed alternatives at athina-evals alternatives and evals alternatives (athina-evals markdown twin, evals 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 evals?
- athina-evals: Dormant. evals: 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 athina-evals and evals?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: athina-evals trust report; evals trust report.