Comparison
athina-evals vs SciEvalKit
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 SciEvalKit if sciEvalKit is a unified evaluation toolkit and leaderboard designed to rigorously assess the scientific capabilities of large language and vision-language models throughout research processes.
Markdown twin · athina-evals alternatives · SciEvalKit alternatives
GraphCanon updated Sep 9, 2026
7views this month
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Trust & integrity
| Signal | athina-evals | SciEvalKit |
|---|---|---|
| Maintenance | Dormant (447d since push) As of Aug 28, 2026 · github_public_v1 | Active (10d since push) As of Sep 9, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Aug 28, 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 | Published findings 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
- SciEvalKit
- Unified evaluation toolkit and leaderboard for assessing scientific intelligence
Stars
- athina-evals
- 301
- SciEvalKit
- 86
Forks
- athina-evals
- 23
- SciEvalKit
- 13
Open issues
- athina-evals
- 5
- SciEvalKit
- 6
Language
- athina-evals
- Python
- SciEvalKit
- 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.
- SciEvalKit
- SciEvalKit is a unified evaluation toolkit and leaderboard designed to rigorously assess the scientific capabilities of large language and vision-language models throughout research processes.
Persona
- athina-evals
- -
- SciEvalKit
- -
Runtime
- athina-evals
- -
- SciEvalKit
- -
License
- athina-evals
- -
- SciEvalKit
- Apache-2.0
Last pushed
- athina-evals
- Jun 6, 2025
- SciEvalKit
- Aug 30, 2026
Categories
- athina-evals
- Evaluation & Observability
- SciEvalKit
- Evaluation & Observability
Trust and health
Maintenance
- athina-evals
- Dormant (18%)
- SciEvalKit
- Active (82%)
Days since push
- athina-evals
- 447d
- SciEvalKit
- 10d
Open issues (now)
- athina-evals
- 5
- SciEvalKit
- 6
Stars delta
- athina-evals
- 0 (30d)
- SciEvalKit
- +1 (30d)
Open issues delta
- athina-evals
- +2 (30d)
- SciEvalKit
- +3 (30d)
OSV dependency advisories
- athina-evals
- No lockfile (source not queried)
- SciEvalKit
- Published findings
Full report
- athina-evals
- Trust report
- SciEvalKit
- Trust report
Choose athina-evals if…
- Tags unique to athina-evals: evaluation, evaluation-metrics, llm-eval, llm-evaluation-toolkit.
- When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics
- More GitHub stars (301 vs 86) - 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 SciEvalKit if…
- Tags unique to SciEvalKit: agent, ai4science, code-generation, gemini.
- When assessing the scientific intelligence of multimodal models specifically across research stages
- More recently updated (last pushed Aug 30, 2026).
When NOT to use SciEvalKit
- For evaluating general performance without a focus on scientific applications and methodologies
- If your project does not benefit from an evaluation framework centered around vision-language abilities in scientific contexts
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 Aug 28, 2026
- GitHub forks (athina-ai/athina-evals) · observed Aug 28, 2026
- Last push (athina-ai/athina-evals) · observed Jun 6, 2025
- License file (unknown) · observed Aug 28, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (InternScience/SciEvalKit) · observed Sep 9, 2026
- GitHub forks (InternScience/SciEvalKit) · observed Sep 9, 2026
- Last push (InternScience/SciEvalKit) · observed Aug 30, 2026
- License file (Apache-2.0) · observed Sep 9, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: athina-evals 301 · SciEvalKit 86 (synced Aug 28, 2026).
Common questions
- What is the difference between athina-evals and SciEvalKit?
- athina-evals: Python SDK for evaluating LLM generated responses. SciEvalKit: Unified evaluation toolkit and leaderboard for assessing scientific intelligence. See the comparison table for live GitHub stats and shared categories.
- When should I choose athina-evals over SciEvalKit?
- Choose athina-evals over SciEvalKit when Tags unique to athina-evals: evaluation, evaluation-metrics, llm-eval, llm-evaluation-toolkit; When comprehensive evaluation of LLM responses is required, leveraging athina's specific tools and metrics; More GitHub stars (301 vs 86) - visibility, not fit.
- When should I choose SciEvalKit over athina-evals?
- Choose SciEvalKit over athina-evals when Tags unique to SciEvalKit: agent, ai4science, code-generation, gemini; When assessing the scientific intelligence of multimodal models specifically across research stages; More recently updated (last pushed Aug 30, 2026).
- 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 SciEvalKit?
- For evaluating general performance without a focus on scientific applications and methodologies If your project does not benefit from an evaluation framework centered around vision-language abilities in scientific contexts
- Is athina-evals or SciEvalKit more popular on GitHub?
- athina-evals has more GitHub stars (301 vs 86). Stars measure visibility, not whether either tool fits your constraints.
- Are athina-evals and SciEvalKit open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to athina-evals or SciEvalKit?
- GraphCanon lists graph-backed alternatives at athina-evals alternatives and SciEvalKit alternatives (athina-evals markdown twin, SciEvalKit 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 SciEvalKit?
- athina-evals: Dormant. SciEvalKit: 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 SciEvalKit?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: athina-evals trust report; SciEvalKit trust report.