Comparison
lever vs CodeGeeX
Verdict
Pick lever if lever offers support for verifying language-to-code generation through actual code execution; pick CodeGeeX if codeGeeX is an open-source multilingual code generation model, originally developed with MindSpore and compatible with PyTorch through DeepSpeed integration.
Markdown twin · lever alternatives · CodeGeeX alternatives
GraphCanon updated 2w
Trust & integrity
| Signal | lever | CodeGeeX |
|---|---|---|
| Maintenance | Dormant (1127d since push) As of 2w · github_public_v1 | Dormant (719d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2w · github_public_v1 | Not a fork · Organization account As of 3w · 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
- CodeGeeX
- CodeGeeX is an open multilingual code generation model implemented in Mindspore and available via PyTorch.
Stars
- lever
- 90
- CodeGeeX
- 8.8k
Forks
- lever
- 8
- CodeGeeX
- 688
Open issues
- lever
- 2
- CodeGeeX
- 188
Language
- lever
- Python
- CodeGeeX
- Python
Adopt for
- lever
- Lever offers support for verifying language-to-code generation through actual code execution.
- CodeGeeX
- CodeGeeX is an open-source multilingual code generation model, originally developed with MindSpore and compatible with PyTorch through DeepSpeed integration.
Persona
- lever
- -
- CodeGeeX
- -
Runtime
- lever
- -
- CodeGeeX
- -
License
- lever
- Lever's source code is freely available under an MIT License for modification and distribution in both personal and commercial projects.
- CodeGeeX
- Apache-2.0
Last pushed
- lever
- Jul 5, 2023
- CodeGeeX
- Aug 13, 2024
Categories
- lever
- Evaluation & Observability, Model Training
- CodeGeeX
- LLM Frameworks, Model Training
Trust and health
Days since push
- lever
- 1127d
- CodeGeeX
- 719d
Open issues (now)
- lever
- 2
- CodeGeeX
- 188
Owner type
- lever
- User
- CodeGeeX
- Organization
OSV dependency advisories
- lever
- No published findings from this source as of 2026-07-11
- CodeGeeX
- Published findings
Full report
- lever
- Trust report
- CodeGeeX
- Trust report
Shared compatibility
- Python · lever: Python runtime · CodeGeeX: Python runtime
Choose lever if…
- License: lever is MIT, CodeGeeX 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 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 CodeGeeX if…
- License: CodeGeeX is Apache-2.0, lever is MIT.
- Tags unique to CodeGeeX: ai programming tools, code generation, pretrained-models.
- Also covers LLM Frameworks.
- When you require support for multilingual code generation and your project has a Python-based infrastructure with CUDA GPU availability.
When NOT to use CodeGeeX
- If your development environment lacks the necessary dependencies like Python 3.7+, CUDA 11+, PyTorch 1.10+, and DeepSpeed 0.6+.
- In scenarios where an open-source solution is not preferable or when support for exclusively one language's syntax is sufficient.
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 (zai-org/CodeGeeX) · observed Aug 2, 2026
- GitHub forks (zai-org/CodeGeeX) · observed Aug 2, 2026
- Last push (zai-org/CodeGeeX) · observed Aug 13, 2024
- License file (Apache-2.0) · observed Aug 2, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: lever 90 · CodeGeeX 8.8k (synced Aug 5, 2026).
Common questions
- What is the difference between lever and CodeGeeX?
- lever: Supports learning to verify language-to-code generation with execution. CodeGeeX: CodeGeeX is an open multilingual code generation model implemented in Mindspore and available via PyTorch.. See the comparison table for live GitHub stats and shared categories.
- When should I choose lever over CodeGeeX?
- Choose lever over CodeGeeX when License: lever is MIT, CodeGeeX is Apache-2.0; 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 CodeGeeX over lever?
- Choose CodeGeeX over lever when License: CodeGeeX is Apache-2.0, lever is MIT; Tags unique to CodeGeeX: ai programming tools, code generation, pretrained-models; Also covers LLM Frameworks; When you require support for multilingual code generation and your project has a Python-based infrastructure with CUDA GPU availability.
- 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 CodeGeeX?
- If your development environment lacks the necessary dependencies like Python 3.7+, CUDA 11+, PyTorch 1.10+, and DeepSpeed 0.6+. In scenarios where an open-source solution is not preferable or when support for exclusively one language's syntax is sufficient.
- Is lever or CodeGeeX more popular on GitHub?
- CodeGeeX has more GitHub stars (8,809 vs 90). Stars measure visibility, not whether either tool fits your constraints.
- Are lever and CodeGeeX open source?
- Yes - both are open-source projects on GitHub (lever: MIT, CodeGeeX: Apache-2.0).
- Where can I find alternatives to lever or CodeGeeX?
- GraphCanon lists graph-backed alternatives at lever alternatives and CodeGeeX alternatives (lever markdown twin, CodeGeeX 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 CodeGeeX?
- lever: Dormant. CodeGeeX: 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 lever and CodeGeeX?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: lever trust report; CodeGeeX trust report.