--- title: "bigcode-evaluation-harness vs HLCE" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bigcode-project-bigcode-evaluation-harness-vs-humanity-s-last-code-exam-hlce" tools: ["bigcode-project-bigcode-evaluation-harness", "humanity-s-last-code-exam-hlce"] --- # bigcode-evaluation-harness vs HLCE *GraphCanon updated Aug 8, 2026* ## Verdict 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; pick HLCE if hLCE offers evaluation scripts to assess code generation using LLMs, specifically for research purposes. [bigcode-evaluation-harness](https://github.com/bigcode-project/bigcode-evaluation-harness) reports 1.1k GitHub stars, 261 forks, and 96 open issues, last pushed Jul 22, 2025. [HLCE](https://humanity-s-last-code-exam.github.io/website/) has 96 stars, 8 forks, and 1 open issues, last pushed Aug 21, 2025. Figures are from public GitHub metadata via [bigcode-evaluation-harness's repository](https://github.com/bigcode-project/bigcode-evaluation-harness) and [HLCE's repository](https://github.com/Humanity-s-Last-Code-Exam/HLCE). | | [bigcode-evaluation-harness](/tools/bigcode-project-bigcode-evaluation-harness.md) | [HLCE](/tools/humanity-s-last-code-exam-hlce.md) | | --- | --- | --- | | Tagline | A framework for evaluating autoregressive code generation language models. | Source Evaluation scripts for Humanity's Last Code Exam | | Stars | 1,055 | 96 | | Forks | 261 | 8 | | Open issues | 96 | 1 | | Language | Python | Python | | Adopt for | bigcode-evaluation-harness is tailored towards evaluating autoregressive code generation models via Python and Docker containers for secure and reproducible execution environments. | HLCE offers evaluation scripts to assess code generation using LLMs, specifically for research purposes. | | Persona | - | - | | Runtime | - | - | | License | bigcode-evaluation-harness is distributed under the Apache-2.0 license. | - | | Categories | Evaluation & Observability | Evaluation & Observability, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [bigcode-evaluation-harness](/tools/bigcode-project-bigcode-evaluation-harness.md) | [HLCE](/tools/humanity-s-last-code-exam-hlce.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 378d | 352d | | Open issues (now) | 96 | 1 | | Full report | [trust report](/tools/bigcode-project-bigcode-evaluation-harness/trust.md) | [trust report](/tools/humanity-s-last-code-exam-hlce/trust.md) | ## 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. ## Decision facts: HLCE - **Adopt for:** HLCE offers evaluation scripts to assess code generation using LLMs, specifically for research purposes. ## Choose when ### 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. ### Choose HLCE if… - Tags unique to HLCE: benchmark, codegen, codellm, llm-evaluation. - Also covers LLM Frameworks. - When you are researching the capabilities of language models in generating code and need benchmarking tools that focus on this aspect exclusively. ## 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. ## When NOT to use HLCE - If you require tools that cater to general-purpose evaluation beyond the scope of LLM code generation in a research context. - When proprietary or non-research licenses are necessary, since HLCE does not detail its licensing beyond being for research purposes only. ## Common questions ### What is the difference between bigcode-evaluation-harness and HLCE? bigcode-evaluation-harness: A framework for evaluating autoregressive code generation language models.. HLCE: Source Evaluation scripts for Humanity's Last Code Exam. See the comparison table for live GitHub stats and shared categories. ### When should I choose bigcode-evaluation-harness over HLCE? Choose bigcode-evaluation-harness over HLCE 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 choose HLCE over bigcode-evaluation-harness? Choose HLCE over bigcode-evaluation-harness when Tags unique to HLCE: benchmark, codegen, codellm, llm-evaluation; Also covers LLM Frameworks; When you are researching the capabilities of language models in generating code and need benchmarking tools that focus on this aspect exclusively. ### 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. ### When should I avoid HLCE? If you require tools that cater to general-purpose evaluation beyond the scope of LLM code generation in a research context. When proprietary or non-research licenses are necessary, since HLCE does not detail its licensing beyond being for research purposes only. ### Is bigcode-evaluation-harness or HLCE more popular on GitHub? bigcode-evaluation-harness has more GitHub stars (1,055 vs 96). Stars measure visibility, not whether either tool fits your constraints. ### Are bigcode-evaluation-harness and HLCE open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to bigcode-evaluation-harness or HLCE? GraphCanon lists graph-backed alternatives at [bigcode-evaluation-harness alternatives](/tools/bigcode-project-bigcode-evaluation-harness/alternatives) and [HLCE alternatives](/tools/humanity-s-last-code-exam-hlce/alternatives) ([bigcode-evaluation-harness markdown twin](/tools/bigcode-project-bigcode-evaluation-harness/alternatives.md), [HLCE markdown twin](/tools/humanity-s-last-code-exam-hlce/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/bigcode-project-bigcode-evaluation-harness-vs-humanity-s-last-code-exam-hlce.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, bigcode-evaluation-harness or HLCE? bigcode-evaluation-harness: Dormant. HLCE: Slowing. 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 bigcode-evaluation-harness and HLCE? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [bigcode-evaluation-harness trust report](/tools/bigcode-project-bigcode-evaluation-harness/trust); [HLCE trust report](/tools/humanity-s-last-code-exam-hlce/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=bigcode-project-bigcode-evaluation-harness`](/api/graphcanon/graph?tool=bigcode-project-bigcode-evaluation-harness) - 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/_