--- title: "code-eval vs LiveCodeBench" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/abacaj-code-eval-vs-livecodebench-livecodebench" tools: ["abacaj-code-eval", "livecodebench-livecodebench"] --- # code-eval vs LiveCodeBench *GraphCanon updated Oct 8, 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 LiveCodeBench if liveCodeBench offers an in-depth approach to evaluating large language models specifically for code tasks such as generation and repair. [code-eval](https://github.com/abacaj/code-eval) reports 432 GitHub stars, 36 forks, and 5 open issues, last pushed Sep 12, 2023. [LiveCodeBench](https://livecodebench.github.io/) has 958 stars, 206 forks, and 49 open issues, last pushed Jul 16, 2025. Figures are from public GitHub metadata via [code-eval's repository](https://github.com/abacaj/code-eval) and [LiveCodeBench's repository](https://github.com/LiveCodeBench/LiveCodeBench). | | [code-eval](/tools/abacaj-code-eval.md) | [LiveCodeBench](/tools/livecodebench-livecodebench.md) | | --- | --- | --- | | Tagline | Run evaluation on LLMs using human-eval benchmark. | Holistic and contamination-free evaluation of large language models for code | | Stars | 432 | 958 | | Forks | 36 | 206 | | Open issues | 5 | 49 | | Language | Python | Python | | Adopt for | code-eval assesses large language models with the human-eval benchmark to provide insights into code generation reliability. | LiveCodeBench offers an in-depth approach to evaluating large language models specifically for code tasks such as generation and repair. | | 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) | [LiveCodeBench](/tools/livecodebench-livecodebench.md) | | --- | --- | --- | | Days since push | 1120d | 449d | | Open issues (now) | 5 | 49 | | Stars delta | +1 (30d) | +22 (30d) | | Open issues delta | 0 (30d) | +6 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/abacaj-code-eval/trust.md) | [trust report](/tools/livecodebench-livecodebench/trust.md) | ## Shared compatibility - **Python**: [code-eval](/tools/abacaj-code-eval.md) - Python runtime; [LiveCodeBench](/tools/livecodebench-livecodebench.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: LiveCodeBench - **Adopt for:** LiveCodeBench offers an in-depth approach to evaluating large language models specifically for code tasks such as generation and repair. ## 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 LiveCodeBench if… - Tags unique to LiveCodeBench: code-execution, code-generation, code-repair, gpt-4. - When you need a holistic method to assess the effectiveness of LLMs in code tasks without risking contamination by earlier outputs or data leakage. - More GitHub stars (958 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 LiveCodeBench - For broad, non-code-specific model assessments where a more generalized evaluation tool would suffice. - If your project is not compatible with Python 3.11 or if you do not want to use the uv dependency manager recommended by LiveCodeBench. ## Common questions ### What is the difference between code-eval and LiveCodeBench? code-eval: Run evaluation on LLMs using human-eval benchmark.. LiveCodeBench: Holistic and contamination-free evaluation of large language models for code. See the comparison table for live GitHub stats and shared categories. ### When should I choose code-eval over LiveCodeBench? Choose code-eval over LiveCodeBench 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 LiveCodeBench over code-eval? Choose LiveCodeBench over code-eval when Tags unique to LiveCodeBench: code-execution, code-generation, code-repair, gpt-4; When you need a holistic method to assess the effectiveness of LLMs in code tasks without risking contamination by earlier outputs or data leakage; More GitHub stars (958 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 LiveCodeBench? For broad, non-code-specific model assessments where a more generalized evaluation tool would suffice. If your project is not compatible with Python 3.11 or if you do not want to use the uv dependency manager recommended by LiveCodeBench. ### Is code-eval or LiveCodeBench more popular on GitHub? LiveCodeBench has more GitHub stars (958 vs 432). Stars measure visibility, not whether either tool fits your constraints. ### Are code-eval and LiveCodeBench open source? Yes - both are open-source projects on GitHub (code-eval: MIT, LiveCodeBench: MIT). ### Where can I find alternatives to code-eval or LiveCodeBench? GraphCanon lists graph-backed alternatives at [code-eval alternatives](/tools/abacaj-code-eval/alternatives) and [LiveCodeBench alternatives](/tools/livecodebench-livecodebench/alternatives) ([code-eval markdown twin](/tools/abacaj-code-eval/alternatives.md), [LiveCodeBench markdown twin](/tools/livecodebench-livecodebench/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-livecodebench-livecodebench.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, code-eval or LiveCodeBench? code-eval: Dormant. LiveCodeBench: 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 code-eval and LiveCodeBench? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [code-eval trust report](/tools/abacaj-code-eval/trust); [LiveCodeBench trust report](/tools/livecodebench-livecodebench/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/_