--- title: "CommonGen-Eval vs deepeval" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/allenai-commongen-eval-vs-confident-ai-deepeval" tools: ["allenai-commongen-eval", "confident-ai-deepeval"] --- # CommonGen-Eval vs deepeval *GraphCanon updated Sep 20, 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 deepeval if deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies. [CommonGen-Eval](https://inklab.usc.edu/CommonGen/) reports 95 GitHub stars, 3 forks, and 1 open issues, last pushed Mar 21, 2024. [deepeval](https://deepeval.com) has 18k stars, 2.0k forks, and 624 open issues, last pushed Sep 18, 2026. Figures are from public GitHub metadata via [CommonGen-Eval's repository](https://github.com/allenai/CommonGen-Eval) and [deepeval's repository](https://github.com/confident-ai/deepeval). | | [CommonGen-Eval](/tools/allenai-commongen-eval.md) | [deepeval](/tools/confident-ai-deepeval.md) | | --- | --- | --- | | Tagline | Evaluating LLMs with CommonGen-Lite | LLM Evaluation Framework. | | Stars | 95 | 18,342 | | Forks | 3 | 1,953 | | Open issues | 1 | 624 | | 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. | Deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 License | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [CommonGen-Eval](/tools/allenai-commongen-eval.md) | [deepeval](/tools/confident-ai-deepeval.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 901d | 1d | | Open issues (now) | 1 | 624 | | Stars delta | 0 (30d) | +1.1k (30d) | | Open issues delta | 0 (30d) | +220 (30d) | | Full report | [trust report](/tools/allenai-commongen-eval/trust.md) | [trust report](/tools/confident-ai-deepeval/trust.md) | ## Shared compatibility - **Python**: [CommonGen-Eval](/tools/allenai-commongen-eval.md) - Python runtime; [deepeval](/tools/confident-ai-deepeval.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: deepeval - **Requirements:** Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities. - **Adopt for:** Deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies. - **License detail:** Apache-2.0 License ## Choose when ### Choose CommonGen-Eval if… - Requirements: Install Python dependencies using `pip install -r requirements.txt`; Download necessary Spacy models with `python -m spacy download en_core_web_lg`. - 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. - Leaner open-issue backlog (1). ### Choose deepeval if… - Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities.. - Tags unique to deepeval: metrics. - When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics. ## 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 deepeval - For small-scale applications that do not require the depth of metrics and evaluations offered by Deepeval, as it might be overkill. - In situations where there is a need for real-time performance monitoring, since Deepeval focuses more on post-development evaluation rather than continuous runtime analysis. ## Common questions ### What is the difference between CommonGen-Eval and deepeval? CommonGen-Eval: Evaluating LLMs with CommonGen-Lite. deepeval: LLM Evaluation Framework.. See the comparison table for live GitHub stats and shared categories. ### When should I choose CommonGen-Eval over deepeval? Choose CommonGen-Eval over deepeval when Requirements: Install Python dependencies using `pip install -r requirements.txt`; Download necessary Spacy models with `python -m spacy download en_core_web_lg`; 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; Leaner open-issue backlog (1). ### When should I choose deepeval over CommonGen-Eval? Choose deepeval over CommonGen-Eval when Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities.; Tags unique to deepeval: metrics; When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics. ### 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 deepeval? For small-scale applications that do not require the depth of metrics and evaluations offered by Deepeval, as it might be overkill. In situations where there is a need for real-time performance monitoring, since Deepeval focuses more on post-development evaluation rather than continuous runtime analysis. ### Is CommonGen-Eval or deepeval more popular on GitHub? deepeval has more GitHub stars (18,342 vs 95). Stars measure visibility, not whether either tool fits your constraints. ### Are CommonGen-Eval and deepeval open source? Yes - both are open-source projects on GitHub (CommonGen-Eval: Apache-2.0, deepeval: Apache-2.0). ### Where can I find alternatives to CommonGen-Eval or deepeval? GraphCanon lists graph-backed alternatives at [CommonGen-Eval alternatives](/tools/allenai-commongen-eval/alternatives) and [deepeval alternatives](/tools/confident-ai-deepeval/alternatives) ([CommonGen-Eval markdown twin](/tools/allenai-commongen-eval/alternatives.md), [deepeval markdown twin](/tools/confident-ai-deepeval/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-confident-ai-deepeval.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, CommonGen-Eval or deepeval? CommonGen-Eval: Dormant. deepeval: 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 CommonGen-Eval and deepeval? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [CommonGen-Eval trust report](/tools/allenai-commongen-eval/trust); [deepeval trust report](/tools/confident-ai-deepeval/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/_