--- title: "code-eval vs lighteval" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/abacaj-code-eval-vs-huggingface-lighteval" tools: ["abacaj-code-eval", "huggingface-lighteval"] --- # code-eval vs lighteval *GraphCanon updated Oct 12, 2026* ## Verdict Pick code-eval if code-eval assesses large language models with the human-eval benchmark to provide insights into code generation reliability; pick lighteval if lighteval is designed for evaluating language models across multiple backends. It integrates well with Hugging Face and provides a wide range of extras, making it particularly handy in non-Windows environments. [code-eval](https://github.com/abacaj/code-eval) reports 432 GitHub stars, 36 forks, and 5 open issues, last pushed Sep 12, 2023. [lighteval](https://huggingface.co/docs/lighteval/en/index) has 2.6k stars, 576 forks, and 437 open issues, last pushed Oct 6, 2026. Figures are from public GitHub metadata via [code-eval's repository](https://github.com/abacaj/code-eval) and [lighteval's repository](https://github.com/huggingface/lighteval). | | [code-eval](/tools/abacaj-code-eval.md) | [lighteval](/tools/huggingface-lighteval.md) | | --- | --- | --- | | Tagline | Run evaluation on LLMs using human-eval benchmark. | All-in-one toolkit for evaluating LLMs across multiple backends | | Stars | 432 | 2,554 | | Forks | 36 | 576 | | Open issues | 5 | 437 | | Language | Python | Python | | Adopt for | code-eval assesses large language models with the human-eval benchmark to provide insights into code generation reliability. | Lighteval is designed for evaluating language models across multiple backends. It integrates well with Hugging Face and provides a wide range of extras, making it particularly handy in non-Windows environments. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Evaluation & Observability | Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [code-eval](/tools/abacaj-code-eval.md) | [lighteval](/tools/huggingface-lighteval.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 1120d | 5d | | Open issues (now) | 5 | 437 | | Stars delta | +1 (30d) | +19 (30d) | | Open issues delta | 0 (30d) | +32 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/abacaj-code-eval/trust.md) | [trust report](/tools/huggingface-lighteval/trust.md) | ## Shared compatibility - **Python**: [code-eval](/tools/abacaj-code-eval.md) - Python runtime; [lighteval](/tools/huggingface-lighteval.md) - Python runtime ## Decision facts: code-eval - **Adopt for:** code-eval assesses large language models with the human-eval benchmark to provide insights into code generation reliability. ## Decision facts: lighteval - **Adopt for:** Lighteval is designed for evaluating language models across multiple backends. It integrates well with Hugging Face and provides a wide range of extras, making it particularly handy in non-Windows environments. ## Choose when ### Choose code-eval if… - Tags unique to code-eval: humaneval, wizardcoder. - When you need clear comparisons of pass rates for different LLMs using standardized tests - Leaner open-issue backlog (5). ### Choose lighteval if… - Tags unique to lighteval: evaluation, evaluation-framework, evaluation-metrics, huggingface. - When you need to evaluate the performance of various LLMs on different backend infrastructures, especially if you are working within Mac/Linux environments. - More GitHub stars (2.6k vs 432) - visibility, not fit. ## 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 ## When NOT to use lighteval - Avoid Lighteval for evaluations on Windows systems as it is currently untested and not supported there. - Should you require a solution that does not integrate with or depend on the Hugging Face ecosystem, Lighteval might not fulfill your needs. ## Common questions ### What is the difference between code-eval and lighteval? code-eval: Run evaluation on LLMs using human-eval benchmark.. lighteval: All-in-one toolkit for evaluating LLMs across multiple backends. See the comparison table for live GitHub stats and shared categories. ### When should I choose code-eval over lighteval? Choose code-eval over lighteval when Tags unique to code-eval: humaneval, wizardcoder; When you need clear comparisons of pass rates for different LLMs using standardized tests; Leaner open-issue backlog (5). ### When should I choose lighteval over code-eval? Choose lighteval over code-eval when Tags unique to lighteval: evaluation, evaluation-framework, evaluation-metrics, huggingface; When you need to evaluate the performance of various LLMs on different backend infrastructures, especially if you are working within Mac/Linux environments; More GitHub stars (2.6k vs 432) - visibility, not fit. ### 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 lighteval? Avoid Lighteval for evaluations on Windows systems as it is currently untested and not supported there. Should you require a solution that does not integrate with or depend on the Hugging Face ecosystem, Lighteval might not fulfill your needs. ### Is code-eval or lighteval more popular on GitHub? lighteval has more GitHub stars (2,554 vs 432). Stars measure visibility, not whether either tool fits your constraints. ### Are code-eval and lighteval open source? Yes - both are open-source projects on GitHub (code-eval: MIT, lighteval: MIT). ### Where can I find alternatives to code-eval or lighteval? GraphCanon lists graph-backed alternatives at [code-eval alternatives](/tools/abacaj-code-eval/alternatives) and [lighteval alternatives](/tools/huggingface-lighteval/alternatives) ([code-eval markdown twin](/tools/abacaj-code-eval/alternatives.md), [lighteval markdown twin](/tools/huggingface-lighteval/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/abacaj-code-eval-vs-huggingface-lighteval.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, code-eval or lighteval? code-eval: Dormant. lighteval: 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 code-eval and lighteval? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [code-eval trust report](/tools/abacaj-code-eval/trust); [lighteval trust report](/tools/huggingface-lighteval/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=abacaj-code-eval`](/api/graphcanon/graph?tool=abacaj-code-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/_