--- title: "bigcode-evaluation-harness vs lever" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bigcode-project-bigcode-evaluation-harness-vs-niansong1996-lever" tools: ["bigcode-project-bigcode-evaluation-harness", "niansong1996-lever"] --- # bigcode-evaluation-harness vs lever *GraphCanon updated Aug 5, 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 lever if lever offers support for verifying language-to-code generation through actual code execution. [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. [lever](https://arxiv.org/abs/2302.08468) has 90 stars, 8 forks, and 2 open issues, last pushed Jul 5, 2023. Figures are from public GitHub metadata via [bigcode-evaluation-harness's repository](https://github.com/bigcode-project/bigcode-evaluation-harness) and [lever's repository](https://github.com/niansong1996/lever). | | [bigcode-evaluation-harness](/tools/bigcode-project-bigcode-evaluation-harness.md) | [lever](/tools/niansong1996-lever.md) | | --- | --- | --- | | Tagline | A framework for evaluating autoregressive code generation language models. | Supports learning to verify language-to-code generation with execution | | Stars | 1,055 | 90 | | Forks | 261 | 8 | | Open issues | 96 | 2 | | 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. | Lever offers support for verifying language-to-code generation through actual code execution. | | Persona | - | - | | Runtime | - | - | | License | bigcode-evaluation-harness is distributed under the Apache-2.0 license. | Lever's source code is freely available under an MIT License for modification and distribution in both personal and commercial projects. | | Categories | Evaluation & Observability | Evaluation & Observability, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [bigcode-evaluation-harness](/tools/bigcode-project-bigcode-evaluation-harness.md) | [lever](/tools/niansong1996-lever.md) | | --- | --- | --- | | Days since push | 378d | 1127d | | Open issues (now) | 96 | 2 | | Owner type | Organization | User | | Full report | [trust report](/tools/bigcode-project-bigcode-evaluation-harness/trust.md) | [trust report](/tools/niansong1996-lever/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: lever - **Requirements:** All of the pipelines have been tested on Linux machines only, requiring possibly custom `tree-sitter` parsers for other platforms. - **Adopt for:** Lever offers support for verifying language-to-code generation through actual code execution. - **License detail:** Lever's source code is freely available under an MIT License for modification and distribution in both personal and commercial projects. ## Choose when ### Choose bigcode-evaluation-harness if… - License: bigcode-evaluation-harness is Apache-2.0, lever is MIT. - 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 lever if… - License: lever is MIT, bigcode-evaluation-harness is Apache-2.0. - Requirements: All of the pipelines have been tested on Linux machines only, requiring possibly custom `tree-sitter` parsers for other platforms.. - Tags unique to lever: code verification, execution based verification, language-to-code. - Also covers Model Training. - When the development team needs to verify accuracy of generated code from language inputs based on execution, and has access to Linux machines to ensure seamless functionality. ## 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 lever - Avoid Lever if developing in an environment other than Linux as it requires the use of tree-sitter parsers, which may not be compatible with your system. - Do not choose Lever if you seek a tool that does not require setting up a conda environment and installing specific dependencies to operate. ## Common questions ### What is the difference between bigcode-evaluation-harness and lever? bigcode-evaluation-harness: A framework for evaluating autoregressive code generation language models.. lever: Supports learning to verify language-to-code generation with execution. See the comparison table for live GitHub stats and shared categories. ### When should I choose bigcode-evaluation-harness over lever? Choose bigcode-evaluation-harness over lever when License: bigcode-evaluation-harness is Apache-2.0, lever is MIT; 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 lever over bigcode-evaluation-harness? Choose lever over bigcode-evaluation-harness when License: lever is MIT, bigcode-evaluation-harness is Apache-2.0; Requirements: All of the pipelines have been tested on Linux machines only, requiring possibly custom `tree-sitter` parsers for other platforms.; Tags unique to lever: code verification, execution based verification, language-to-code; Also covers Model Training; When the development team needs to verify accuracy of generated code from language inputs based on execution, and has access to Linux machines to ensure seamless functionality. ### 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 lever? Avoid Lever if developing in an environment other than Linux as it requires the use of tree-sitter parsers, which may not be compatible with your system. Do not choose Lever if you seek a tool that does not require setting up a conda environment and installing specific dependencies to operate. ### Is bigcode-evaluation-harness or lever more popular on GitHub? bigcode-evaluation-harness has more GitHub stars (1,055 vs 90). Stars measure visibility, not whether either tool fits your constraints. ### Are bigcode-evaluation-harness and lever open source? Yes - both are open-source projects on GitHub (bigcode-evaluation-harness: Apache-2.0, lever: MIT). ### Where can I find alternatives to bigcode-evaluation-harness or lever? GraphCanon lists graph-backed alternatives at [bigcode-evaluation-harness alternatives](/tools/bigcode-project-bigcode-evaluation-harness/alternatives) and [lever alternatives](/tools/niansong1996-lever/alternatives) ([bigcode-evaluation-harness markdown twin](/tools/bigcode-project-bigcode-evaluation-harness/alternatives.md), [lever markdown twin](/tools/niansong1996-lever/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-niansong1996-lever.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 lever? bigcode-evaluation-harness: Dormant. lever: 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 bigcode-evaluation-harness and lever? 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); [lever trust report](/tools/niansong1996-lever/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/_