Comparison
lever vs CodeRL
Verdict
Pick lever if lever offers support for verifying language-to-code generation through actual code execution; pick CodeRL if codeRL is an advanced tool that uses pretrained models and deep reinforcement learning to generate code.
Markdown twin · lever alternatives · CodeRL alternatives
GraphCanon updated 2w
Trust & integrity
| Signal | lever | CodeRL |
|---|---|---|
| Maintenance | Dormant (1127d since push) As of 2w · github_public_v1 | Steady (63d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2w · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | No published findings from this source as of 2026-07-11 As of 1mo · osv@v1 | Published findings As of 1mo · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- lever
- Supports learning to verify language-to-code generation with execution
- CodeRL
- CodeRL: Combines pretrained models and reinforcement learning for code generation.
Stars
- lever
- 90
- CodeRL
- 574
Forks
- lever
- 8
- CodeRL
- 69
Open issues
- lever
- 2
- CodeRL
- 42
Language
- lever
- Python
- CodeRL
- Python
Adopt for
- lever
- Lever offers support for verifying language-to-code generation through actual code execution.
- CodeRL
- CodeRL is an advanced tool that uses pretrained models and deep reinforcement learning to generate code.
Persona
- lever
- -
- CodeRL
- -
Runtime
- lever
- -
- CodeRL
- -
License
- lever
- Lever's source code is freely available under an MIT License for modification and distribution in both personal and commercial projects.
- CodeRL
- BSD-3-Clause
Last pushed
- lever
- Jul 5, 2023
- CodeRL
- Jun 2, 2026
Categories
- lever
- Evaluation & Observability, Model Training
- CodeRL
- Developer Tools, Model Training
Trust and health
Maintenance
- lever
- Dormant (18%)
- CodeRL
- Steady (60%)
Days since push
- lever
- 1127d
- CodeRL
- 63d
Open issues (now)
- lever
- 2
- CodeRL
- 42
Owner type
- lever
- User
- CodeRL
- Organization
OSV dependency advisories
- lever
- No published findings from this source as of 2026-07-11
- CodeRL
- Published findings
Full report
- lever
- Trust report
- CodeRL
- Trust report
Shared compatibility
- Python · lever: Python runtime · CodeRL: Python runtime
Choose lever if…
- License: lever is MIT, CodeRL is BSD-3-Clause.
- 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 Evaluation & Observability.
- 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 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.
Choose CodeRL if…
- License: CodeRL is BSD-3-Clause, lever is MIT.
- Tags unique to CodeRL: ai, codegeneration, languagemodel, machinelearning.
- Also covers Developer Tools.
- When you need to generate complex and context-aware code snippets utilizing the latest in reinforcement learning techniques.
When NOT to use CodeRL
- Avoid if your project requires only simple, quick code generation without deep reinforcement learning support.
- Do not use if compatibility with versions of the Hugging Face transformers library other than 4.16.1 is critical to avoid potential issues.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (niansong1996/lever) · observed Aug 5, 2026
- GitHub forks (niansong1996/lever) · observed Aug 5, 2026
- Last push (niansong1996/lever) · observed Jul 5, 2023
- License file (MIT) · observed Aug 5, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (salesforce/CodeRL) · observed Aug 5, 2026
- GitHub forks (salesforce/CodeRL) · observed Aug 5, 2026
- Last push (salesforce/CodeRL) · observed Jun 2, 2026
- License file (BSD-3-Clause) · observed Aug 5, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: lever 90 · CodeRL 574 (synced Aug 5, 2026).
Common questions
- What is the difference between lever and CodeRL?
- lever: Supports learning to verify language-to-code generation with execution. CodeRL: CodeRL: Combines pretrained models and reinforcement learning for code generation.. See the comparison table for live GitHub stats and shared categories.
- When should I choose lever over CodeRL?
- Choose lever over CodeRL when License: lever is MIT, CodeRL is BSD-3-Clause; Requirements: All of the pipelines have been tested on Linux machines only, requiring possibly custom
tree-sitterparsers for other platforms.; Tags unique to lever: code verification, execution based verification, language-to-code; Also covers Evaluation & Observability; 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 choose CodeRL over lever?
- Choose CodeRL over lever when License: CodeRL is BSD-3-Clause, lever is MIT; Tags unique to CodeRL: ai, codegeneration, languagemodel, machinelearning; Also covers Developer Tools; When you need to generate complex and context-aware code snippets utilizing the latest in reinforcement learning techniques.
- 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.
- When should I avoid CodeRL?
- Avoid if your project requires only simple, quick code generation without deep reinforcement learning support. Do not use if compatibility with versions of the Hugging Face transformers library other than 4.16.1 is critical to avoid potential issues.
- Is lever or CodeRL more popular on GitHub?
- CodeRL has more GitHub stars (574 vs 90). Stars measure visibility, not whether either tool fits your constraints.
- Are lever and CodeRL open source?
- Yes - both are open-source projects on GitHub (lever: MIT, CodeRL: BSD-3-Clause).
- Where can I find alternatives to lever or CodeRL?
- GraphCanon lists graph-backed alternatives at lever alternatives and CodeRL alternatives (lever markdown twin, CodeRL markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, lever or CodeRL?
- lever: Dormant. CodeRL: Steady. 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 lever and CodeRL?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: lever trust report; CodeRL trust report.