Comparison
code-eval vs CommonGen-Eval
Verdict
Pick code-eval if code-eval assesses large language models with the human-eval benchmark to provide insights into code generation reliability; pick CommonGen-Eval if commonGen-Eval is designed to evaluate large language models using the CommonGen-Lite dataset, focusing on generating diverse phrases and sentences.
Markdown twin · code-eval alternatives · CommonGen-Eval alternatives
GraphCanon updated Oct 6, 2026
10views this month
Trust & integrity
| Signal | code-eval | CommonGen-Eval |
|---|---|---|
| Maintenance | Dormant (1120d since push) As of Oct 6, 2026 · github_public_v1 | Dormant (901d since push) As of Sep 8, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Oct 6, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 8, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings 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
- code-eval
- Run evaluation on LLMs using human-eval benchmark.
- CommonGen-Eval
- Evaluating LLMs with CommonGen-Lite
Stars
- code-eval
- 432
- CommonGen-Eval
- 95
Forks
- code-eval
- 36
- CommonGen-Eval
- 3
Open issues
- code-eval
- 5
- CommonGen-Eval
- 1
Language
- code-eval
- Python
- CommonGen-Eval
- Python
Adopt for
- code-eval
- code-eval assesses large language models with the human-eval benchmark to provide insights into code generation reliability.
- CommonGen-Eval
- CommonGen-Eval is designed to evaluate large language models using the CommonGen-Lite dataset, focusing on generating diverse phrases and sentences.
Persona
- code-eval
- -
- CommonGen-Eval
- -
Runtime
- code-eval
- -
- CommonGen-Eval
- -
License
- code-eval
- MIT
- CommonGen-Eval
- Apache-2.0
Last pushed
- code-eval
- Sep 12, 2023
- CommonGen-Eval
- Mar 21, 2024
Categories
- code-eval
- Evaluation & Observability
- CommonGen-Eval
- Evaluation & Observability
Trust and health
Days since push
- code-eval
- 1120d
- CommonGen-Eval
- 901d
Open issues (now)
- code-eval
- 5
- CommonGen-Eval
- 1
Stars delta
- code-eval
- +1 (30d)
- CommonGen-Eval
- 0 (30d)
Owner type
- code-eval
- User
- CommonGen-Eval
- Organization
Full report
- code-eval
- Trust report
- CommonGen-Eval
- Trust report
Shared compatibility
- Python · code-eval: Python runtime · CommonGen-Eval: Python runtime
Choose code-eval if…
- License: code-eval is MIT, CommonGen-Eval is Apache-2.0.
- Tags unique to code-eval: humaneval, wizardcoder.
- When you need clear comparisons of pass rates for different LLMs using standardized tests
When NOT to use code-eval
- If the tool's results do not correlate well with the official published benchmarks due to unknown prompt differences
- For real-time or dynamic evaluations as this repo offers pre-computed static results only
Choose CommonGen-Eval if…
- License: CommonGen-Eval is Apache-2.0, code-eval is MIT.
- Requirements: Install Python dependencies using `pip install -r requirements.txt`; Download necessary Spacy models with `python -m spacy download en_core_web_lg`.
- Tags unique to CommonGen-Eval: evaluation, llm-evaluation.
- Use CommonGen-Eval when you need to assess how well an LLM can generate a diverse set of common-sense facts or statements based on given concepts.
When NOT to use CommonGen-Eval
- Avoid using CommonGen-Eval if your evaluation priorities align more closely with task-specific benchmarks outside of general-language diversification.
- Do not use this tool if your project requires an evaluation framework that focuses heavily on the ability to answer specific factual questions or handle domain-specific language.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (abacaj/code-eval) · observed Oct 6, 2026
- GitHub forks (abacaj/code-eval) · observed Oct 6, 2026
- Last push (abacaj/code-eval) · observed Sep 12, 2023
- License file (MIT) · observed Oct 6, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (allenai/CommonGen-Eval) · observed Sep 20, 2026
- GitHub forks (allenai/CommonGen-Eval) · observed Sep 20, 2026
- Last push (allenai/CommonGen-Eval) · observed Mar 21, 2024
- 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: code-eval 432 · CommonGen-Eval 95 (synced Oct 6, 2026).
Common questions
- What is the difference between code-eval and CommonGen-Eval?
- code-eval: Run evaluation on LLMs using human-eval benchmark.. CommonGen-Eval: Evaluating LLMs with CommonGen-Lite. See the comparison table for live GitHub stats and shared categories.
- When should I choose code-eval over CommonGen-Eval?
- Choose code-eval over CommonGen-Eval when License: code-eval is MIT, CommonGen-Eval is Apache-2.0; Tags unique to code-eval: humaneval, wizardcoder; When you need clear comparisons of pass rates for different LLMs using standardized tests.
- When should I choose CommonGen-Eval over code-eval?
- Choose CommonGen-Eval over code-eval when License: CommonGen-Eval is Apache-2.0, code-eval is MIT; Requirements: Install Python dependencies using
pip install -r requirements.txt; Download necessary Spacy models withpython -m spacy download en_core_web_lg; Tags unique to CommonGen-Eval: evaluation, llm-evaluation; Use CommonGen-Eval when you need to assess how well an LLM can generate a diverse set of common-sense facts or statements based on given concepts. - When should I avoid code-eval?
- If the tool's results do not correlate well with the official published benchmarks due to unknown prompt differences For real-time or dynamic evaluations as this repo offers pre-computed static results only
- When should I avoid CommonGen-Eval?
- Avoid using CommonGen-Eval if your evaluation priorities align more closely with task-specific benchmarks outside of general-language diversification. Do not use this tool if your project requires an evaluation framework that focuses heavily on the ability to answer specific factual questions or handle domain-specific language.
- Is code-eval or CommonGen-Eval more popular on GitHub?
- code-eval has more GitHub stars (432 vs 95). Stars measure visibility, not whether either tool fits your constraints.
- Are code-eval and CommonGen-Eval open source?
- Yes - both are open-source projects on GitHub (code-eval: MIT, CommonGen-Eval: Apache-2.0).
- Where can I find alternatives to code-eval or CommonGen-Eval?
- GraphCanon lists graph-backed alternatives at code-eval alternatives and CommonGen-Eval alternatives (code-eval markdown twin, CommonGen-Eval 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, code-eval or CommonGen-Eval?
- code-eval: Dormant. CommonGen-Eval: 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 code-eval and CommonGen-Eval?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: code-eval trust report; CommonGen-Eval trust report.