--- title: "CommonGen-Eval vs bigcode-evaluation-harness" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/allenai-commongen-eval-vs-bigcode-project-bigcode-evaluation-harness" tools: ["allenai-commongen-eval", "bigcode-project-bigcode-evaluation-harness"] --- # CommonGen-Eval vs bigcode-evaluation-harness *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 bigcode-evaluation-harness if bigcode-evaluation-harness is tailored towards evaluating autoregressive code generation models via Python and Docker containers for secure and reproducible execution environments. [CommonGen-Eval](https://inklab.usc.edu/CommonGen/) reports 95 GitHub stars, 3 forks, and 1 open issues, last pushed Mar 21, 2024. [bigcode-evaluation-harness](https://github.com/bigcode-project/bigcode-evaluation-harness) has 1.1k stars, 259 forks, and 96 open issues, last pushed Jul 22, 2025. Figures are from public GitHub metadata via [CommonGen-Eval's repository](https://github.com/allenai/CommonGen-Eval) and [bigcode-evaluation-harness's repository](https://github.com/bigcode-project/bigcode-evaluation-harness). | | [CommonGen-Eval](/tools/allenai-commongen-eval.md) | [bigcode-evaluation-harness](/tools/bigcode-project-bigcode-evaluation-harness.md) | | --- | --- | --- | | Tagline | Evaluating LLMs with CommonGen-Lite | A framework for evaluating autoregressive code generation language models. | | Stars | 95 | 1,058 | | Forks | 3 | 259 | | Open issues | 1 | 96 | | 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. | bigcode-evaluation-harness is tailored towards evaluating autoregressive code generation models via Python and Docker containers for secure and reproducible execution environments. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | bigcode-evaluation-harness is distributed under the 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) | [bigcode-evaluation-harness](/tools/bigcode-project-bigcode-evaluation-harness.md) | | --- | --- | --- | | Days since push | 901d | 409d | | Open issues (now) | 1 | 96 | | Stars delta | 0 (30d) | +3 (30d) | | Full report | [trust report](/tools/allenai-commongen-eval/trust.md) | [trust report](/tools/bigcode-project-bigcode-evaluation-harness/trust.md) | ## 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: bigcode-evaluation-harness - **Requirements:** Users must have Docker installed to leverage the isolated execution environments for model output evaluation. - **Adopt for:** bigcode-evaluation-harness is tailored towards evaluating autoregressive code generation models via Python and Docker containers for secure and reproducible execution environments. - **License detail:** bigcode-evaluation-harness is distributed under the 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`. - 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 bigcode-evaluation-harness if… - Requirements: Users must have Docker installed to leverage the isolated execution environments for model output evaluation.. - Tags unique to bigcode-evaluation-harness: autoregressive-models, code-generation, docker, python. - bigcode-evaluation-harness ships Docker support for self-hosted deployment. - When you need to isolate the evaluation environment from your local development setup, ensuring that no external variables affect the outcomes of model performance assessments. ## 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 bigcode-evaluation-harness - When you require real-time evaluation without the overhead of generating outputs locally and then evaluating them within isolated environments via Docker. - If your model's evaluation process does not necessitate autoregressive setup or the security features provided by Docker, using bigcode-evaluation-harness might introduce unnecessary complexity. ## Common questions ### What is the difference between CommonGen-Eval and bigcode-evaluation-harness? CommonGen-Eval: Evaluating LLMs with CommonGen-Lite. bigcode-evaluation-harness: A framework for evaluating autoregressive code generation language models.. See the comparison table for live GitHub stats and shared categories. ### When should I choose CommonGen-Eval over bigcode-evaluation-harness? Choose CommonGen-Eval over bigcode-evaluation-harness when 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 bigcode-evaluation-harness over CommonGen-Eval? Choose bigcode-evaluation-harness over CommonGen-Eval when Requirements: Users must have Docker installed to leverage the isolated execution environments for model output evaluation.; Tags unique to bigcode-evaluation-harness: autoregressive-models, code-generation, docker, python; bigcode-evaluation-harness ships Docker support for self-hosted deployment; When you need to isolate the evaluation environment from your local development setup, ensuring that no external variables affect the outcomes of model performance assessments. ### 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 bigcode-evaluation-harness? When you require real-time evaluation without the overhead of generating outputs locally and then evaluating them within isolated environments via Docker. If your model's evaluation process does not necessitate autoregressive setup or the security features provided by Docker, using bigcode-evaluation-harness might introduce unnecessary complexity. ### Is CommonGen-Eval or bigcode-evaluation-harness more popular on GitHub? bigcode-evaluation-harness has more GitHub stars (1,058 vs 95). Stars measure visibility, not whether either tool fits your constraints. ### Are CommonGen-Eval and bigcode-evaluation-harness open source? Yes - both are open-source projects on GitHub (CommonGen-Eval: Apache-2.0, bigcode-evaluation-harness: Apache-2.0). ### Where can I find alternatives to CommonGen-Eval or bigcode-evaluation-harness? GraphCanon lists graph-backed alternatives at [CommonGen-Eval alternatives](/tools/allenai-commongen-eval/alternatives) and [bigcode-evaluation-harness alternatives](/tools/bigcode-project-bigcode-evaluation-harness/alternatives) ([CommonGen-Eval markdown twin](/tools/allenai-commongen-eval/alternatives.md), [bigcode-evaluation-harness markdown twin](/tools/bigcode-project-bigcode-evaluation-harness/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-bigcode-project-bigcode-evaluation-harness.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, CommonGen-Eval or bigcode-evaluation-harness? CommonGen-Eval: Dormant. bigcode-evaluation-harness: 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 CommonGen-Eval and bigcode-evaluation-harness? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [CommonGen-Eval trust report](/tools/allenai-commongen-eval/trust); [bigcode-evaluation-harness trust report](/tools/bigcode-project-bigcode-evaluation-harness/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/_