---
title: "CommonGen-Eval vs human-eval"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/allenai-commongen-eval-vs-openai-human-eval"
tools: ["allenai-commongen-eval", "openai-human-eval"]
---

# CommonGen-Eval vs human-eval

*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 human-eval if human-eval is a tool designed for evaluating large language models trained specifically on code through human-written tests.

[CommonGen-Eval](https://inklab.usc.edu/CommonGen/) reports 95 GitHub stars, 3 forks, and 1 open issues, last pushed Mar 21, 2024. [human-eval](https://github.com/openai/human-eval) has 3.3k stars, 452 forks, and 44 open issues, last pushed Jan 17, 2025. Figures are from public GitHub metadata via [CommonGen-Eval's repository](https://github.com/allenai/CommonGen-Eval) and [human-eval's repository](https://github.com/openai/human-eval).

| | [CommonGen-Eval](/tools/allenai-commongen-eval.md) | [human-eval](/tools/openai-human-eval.md) |
| --- | --- | --- |
| Tagline | Evaluating LLMs with CommonGen-Lite | Evaluating Large Language Models Trained on Code |
| Stars | 95 | 3,331 |
| Forks | 3 | 452 |
| Open issues | 1 | 44 |
| 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. | human-eval is a tool designed for evaluating large language models trained specifically on code through human-written tests. |
| Persona | - | - |
| Runtime | - | - |
| License | Apache-2.0 | MIT |
| Categories | Evaluation & Observability | Evaluation & Observability |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [CommonGen-Eval](/tools/allenai-commongen-eval.md) | [human-eval](/tools/openai-human-eval.md) |
| --- | --- | --- |
| Days since push | 870d | 564d |
| Open issues (now) | 1 | 44 |
| Full report | [trust report](/tools/allenai-commongen-eval/trust.md) | [trust report](/tools/openai-human-eval/trust.md) |

## Shared compatibility

- **Python**: [CommonGen-Eval](/tools/allenai-commongen-eval.md) - Python runtime; [human-eval](/tools/openai-human-eval.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: human-eval

- **Hosting:** self hosted - This evaluation framework must be installed and set up in your own environment, ensuring full control over the testing process.
- **Pricing:** freemium - The software is available under an MIT license for free use, yet advanced features or services beyond its core functionality might incur costs.
- **Adopt for:** human-eval is a tool designed for evaluating large language models trained specifically on code through human-written tests.

## Choose when

### Choose CommonGen-Eval if…

- License: CommonGen-Eval is Apache-2.0, human-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.

### Choose human-eval if…

- License: human-eval is MIT, CommonGen-Eval is Apache-2.0.
- This evaluation framework must be installed and set up in your own environment, ensuring full control over the testing process.
- Pricing: The software is available under an MIT license for free use, yet advanced features or services beyond its core functionality might incur costs..
- Tags unique to human-eval: code evaluation, large language models, python.
- When you need to evaluate the performance of AI systems that have been trained exclusively on code datasets, as it allows testing via human-created benchmarks relevant only to code-based models.

## 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 human-eval

- If you are interested in evaluating general natural language processing tasks without coding context, as human-eval is tailored specifically for assessing code-focused AI systems.
- When the required Python version is below 3.7; this tool mandates at least Python 3.7 to ensure compatibility with its dependencies.

## Common questions

### What is the difference between CommonGen-Eval and human-eval?

CommonGen-Eval: Evaluating LLMs with CommonGen-Lite. human-eval: Evaluating Large Language Models Trained on Code. See the comparison table for live GitHub stats and shared categories.

### When should I choose CommonGen-Eval over human-eval?

Choose CommonGen-Eval over human-eval when License: CommonGen-Eval is Apache-2.0, human-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 should I choose human-eval over CommonGen-Eval?

Choose human-eval over CommonGen-Eval when License: human-eval is MIT, CommonGen-Eval is Apache-2.0; This evaluation framework must be installed and set up in your own environment, ensuring full control over the testing process; Pricing: The software is available under an MIT license for free use, yet advanced features or services beyond its core functionality might incur costs.; Tags unique to human-eval: code evaluation, large language models, python; When you need to evaluate the performance of AI systems that have been trained exclusively on code datasets, as it allows testing via human-created benchmarks relevant only to code-based models.

### 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 human-eval?

If you are interested in evaluating general natural language processing tasks without coding context, as human-eval is tailored specifically for assessing code-focused AI systems. When the required Python version is below 3.7; this tool mandates at least Python 3.7 to ensure compatibility with its dependencies.

### Is CommonGen-Eval or human-eval more popular on GitHub?

human-eval has more GitHub stars (3,331 vs 95). Stars measure visibility, not whether either tool fits your constraints.

### Are CommonGen-Eval and human-eval open source?

Yes - both are open-source projects on GitHub (CommonGen-Eval: Apache-2.0, human-eval: MIT).

### Where can I find alternatives to CommonGen-Eval or human-eval?

GraphCanon lists graph-backed alternatives at [CommonGen-Eval alternatives](/tools/allenai-commongen-eval/alternatives) and [human-eval alternatives](/tools/openai-human-eval/alternatives) ([CommonGen-Eval markdown twin](/tools/allenai-commongen-eval/alternatives.md), [human-eval markdown twin](/tools/openai-human-eval/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-human-eval.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, CommonGen-Eval or human-eval?

CommonGen-Eval: Dormant. human-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 CommonGen-Eval and human-eval?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [CommonGen-Eval trust report](/tools/allenai-commongen-eval/trust); [human-eval trust report](/tools/openai-human-eval/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/_