--- title: "CommonGen-Eval vs evals" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/allenai-commongen-eval-vs-openai-evals" tools: ["allenai-commongen-eval", "openai-evals"] --- # CommonGen-Eval vs evals *GraphCanon updated Aug 8, 2026* ## Verdict 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; 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. [CommonGen-Eval](https://inklab.usc.edu/CommonGen/) reports 95 GitHub stars, 3 forks, and 1 open issues, last pushed Mar 21, 2024. [evals](https://github.com/openai/evals) has 19k stars, 3.0k forks, and 213 open issues, last pushed Apr 14, 2026. Figures are from public GitHub metadata via [CommonGen-Eval's repository](https://github.com/allenai/CommonGen-Eval) and [evals's repository](https://github.com/openai/evals). | | [CommonGen-Eval](/tools/allenai-commongen-eval.md) | [evals](/tools/openai-evals.md) | | --- | --- | --- | | Tagline | Evaluating LLMs with CommonGen-Lite | Framework for evaluating LLMs and LLM systems with an open-source registry of benchmarks. | | Stars | 95 | 19,127 | | Forks | 3 | 3,050 | | Open issues | 1 | 213 | | Language | Python | Python | | Adopt for | CommonGen-Eval is designed to evaluate large language models using the CommonGen-Lite dataset, focusing on generating diverse phrases and sentences. | 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 | - | - | | Runtime | - | - | | License | Apache-2.0 | Other | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [CommonGen-Eval](/tools/allenai-commongen-eval.md) | [evals](/tools/openai-evals.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 870d | 115d | | Open issues (now) | 1 | 213 | | Full report | [trust report](/tools/allenai-commongen-eval/trust.md) | [trust report](/tools/openai-evals/trust.md) | ## Shared compatibility - **Python**: [CommonGen-Eval](/tools/allenai-commongen-eval.md) - Python runtime; [evals](/tools/openai-evals.md) - Python runtime ## Decision facts: CommonGen-Eval - **Requirements:** Install Python dependencies using `pip install -r requirements.txt`; Download necessary Spacy models with `python -m spacy download en_core_web_lg` - **Adopt for:** CommonGen-Eval is designed to evaluate large language models using the CommonGen-Lite dataset, focusing on generating diverse phrases and sentences. ## Decision facts: evals - **Adopt for:** 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. ## Choose when ### Choose CommonGen-Eval if… - License: CommonGen-Eval is Apache-2.0, evals is Other. - 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. ### Choose evals if… - License: evals is Other, CommonGen-Eval is Apache-2.0. - Tags unique to evals: benchmarking, custom eval creation, evaluation-framework, large language models. - * 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. ## 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. ## 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 ## Common questions ### What is the difference between CommonGen-Eval and evals? CommonGen-Eval: Evaluating LLMs with CommonGen-Lite. 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 CommonGen-Eval over evals? Choose CommonGen-Eval over evals when License: CommonGen-Eval is Apache-2.0, evals is Other; 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 should I choose evals over CommonGen-Eval? Choose evals over CommonGen-Eval when License: evals is Other, CommonGen-Eval is Apache-2.0; Tags unique to evals: benchmarking, custom eval creation, evaluation-framework, large language models; * 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. ### 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. ### 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 CommonGen-Eval or evals more popular on GitHub? evals has more GitHub stars (19,127 vs 95). Stars measure visibility, not whether either tool fits your constraints. ### Are CommonGen-Eval and evals open source? Yes - both are open-source projects on GitHub (CommonGen-Eval: Apache-2.0, evals: Other). ### Where can I find alternatives to CommonGen-Eval or evals? GraphCanon lists graph-backed alternatives at [CommonGen-Eval alternatives](/tools/allenai-commongen-eval/alternatives) and [evals alternatives](/tools/openai-evals/alternatives) ([CommonGen-Eval markdown twin](/tools/allenai-commongen-eval/alternatives.md), [evals markdown twin](/tools/openai-evals/alternatives.md)), 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](/compare/allenai-commongen-eval-vs-openai-evals.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, CommonGen-Eval or evals? CommonGen-Eval: 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 CommonGen-Eval and evals? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [CommonGen-Eval trust report](/tools/allenai-commongen-eval/trust); [evals trust report](/tools/openai-evals/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=allenai-commongen-eval`](/api/graphcanon/graph?tool=allenai-commongen-eval) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_