Comparison
LLM4Decompile vs CodeGeeX
Verdict
Pick LLM4Decompile if lLM4Decompile uses large language models to reverse engineer binary code into assembly instructions and potentially source code; 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 · LLM4Decompile alternatives · CodeGeeX alternatives
GraphCanon updated 4d
vs
Trust & integrity
| Signal | LLM4Decompile | CodeGeeX |
|---|---|---|
| Maintenance | Slowing (186d since push) As of 4d · github_public_v1 | Dormant (719d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Personal account As of 4d · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | Published findings 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
- LLM4Decompile
- Decompiling Binary Code with Large Language Models
- CodeGeeX
- CodeGeeX is an open multilingual code generation model implemented in Mindspore and available via PyTorch.
Stars
- LLM4Decompile
- 7.0k
- CodeGeeX
- 8.8k
Forks
- LLM4Decompile
- 546
- CodeGeeX
- 688
Open issues
- LLM4Decompile
- 46
- CodeGeeX
- 188
Language
- LLM4Decompile
- Python
- CodeGeeX
- Python
Adopt for
- LLM4Decompile
- LLM4Decompile uses large language models to reverse engineer binary code into assembly instructions and potentially source code.
- CodeGeeX
- CodeGeeX is an open-source multilingual code generation model, originally developed with MindSpore and compatible with PyTorch through DeepSpeed integration.
Persona
- LLM4Decompile
- -
- CodeGeeX
- -
Runtime
- LLM4Decompile
- -
- CodeGeeX
- -
License
- LLM4Decompile
- MIT
- CodeGeeX
- Apache-2.0
Last pushed
- LLM4Decompile
- Feb 12, 2026
- CodeGeeX
- Aug 13, 2024
Categories
- LLM4Decompile
- LLM Frameworks
- CodeGeeX
- LLM Frameworks, Model Training
Trust and health
Maintenance
- LLM4Decompile
- Slowing (36%)
- CodeGeeX
- Dormant (18%)
Days since push
- LLM4Decompile
- 186d
- CodeGeeX
- 719d
Open issues (now)
- LLM4Decompile
- 46
- CodeGeeX
- 188
Stars delta
- LLM4Decompile
- +205 (30d)
- CodeGeeX
- Unknown
Open issues delta
- LLM4Decompile
- 0 (30d)
- CodeGeeX
- Unknown
Owner type
- LLM4Decompile
- User
- CodeGeeX
- Organization
Full report
- LLM4Decompile
- Trust report
- CodeGeeX
- Trust report
Shared compatibility
- Python · LLM4Decompile: Python runtime · CodeGeeX: Python runtime
Choose LLM4Decompile if…
- License: LLM4Decompile is MIT, CodeGeeX is Apache-2.0.
- Pricing: The tool itself is open-source under the MIT license, but using it effectively may require access to specific large language models that could have associated costs..
- Requirements: Min 16 GB RAM; Requires a GPU for optimal performance with the specified model..
- Tags unique to LLM4Decompile: binary, decompile, large language models, reverse-engineering.
- LLM4Decompile ships Docker support for self-hosted deployment.
- When you need a tool that leverages advanced language models for decompiling binaries more effectively than traditional methods.
When NOT to use LLM4Decompile
- Avoid this tool if you require high precision in recreating exact source code, especially for heavily optimized binaries that lose contextual information during compilation.
- Do not use LLM4Decompile when working with less common architectures (e.g., RISC-V) unless explicitly supported or tested by the model.
Choose CodeGeeX if…
- License: CodeGeeX is Apache-2.0, LLM4Decompile is MIT.
- Tags unique to CodeGeeX: ai programming tools, code generation, pretrained-models.
- Also covers Model Training.
- 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 (albertan017/LLM4Decompile) · observed Aug 17, 2026
- GitHub forks (albertan017/LLM4Decompile) · observed Aug 17, 2026
- Last push (albertan017/LLM4Decompile) · observed Feb 12, 2026
- License file (MIT) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 12, 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: LLM4Decompile 7.0k · CodeGeeX 8.8k (synced Aug 17, 2026).
Common questions
- What is the difference between LLM4Decompile and CodeGeeX?
- LLM4Decompile: Decompiling Binary Code with Large Language Models. 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 LLM4Decompile over CodeGeeX?
- Choose LLM4Decompile over CodeGeeX when License: LLM4Decompile is MIT, CodeGeeX is Apache-2.0; Pricing: The tool itself is open-source under the MIT license, but using it effectively may require access to specific large language models that could have associated costs.; Requirements: Min 16 GB RAM; Requires a GPU for optimal performance with the specified model.; Tags unique to LLM4Decompile: binary, decompile, large language models, reverse-engineering; LLM4Decompile ships Docker support for self-hosted deployment; When you need a tool that leverages advanced language models for decompiling binaries more effectively than traditional methods.
- When should I choose CodeGeeX over LLM4Decompile?
- Choose CodeGeeX over LLM4Decompile when License: CodeGeeX is Apache-2.0, LLM4Decompile is MIT; Tags unique to CodeGeeX: ai programming tools, code generation, pretrained-models; Also covers Model Training; When you require support for multilingual code generation and your project has a Python-based infrastructure with CUDA GPU availability.
- When should I avoid LLM4Decompile?
- Avoid this tool if you require high precision in recreating exact source code, especially for heavily optimized binaries that lose contextual information during compilation. Do not use LLM4Decompile when working with less common architectures (e.g., RISC-V) unless explicitly supported or tested by the model.
- 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 LLM4Decompile or CodeGeeX more popular on GitHub?
- CodeGeeX has more GitHub stars (8,809 vs 6,965). Stars measure visibility, not whether either tool fits your constraints.
- Are LLM4Decompile and CodeGeeX open source?
- Yes - both are open-source projects on GitHub (LLM4Decompile: MIT, CodeGeeX: Apache-2.0).
- Where can I find alternatives to LLM4Decompile or CodeGeeX?
- GraphCanon lists graph-backed alternatives at LLM4Decompile alternatives and CodeGeeX alternatives (LLM4Decompile 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, LLM4Decompile or CodeGeeX?
- LLM4Decompile: Slowing. 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 LLM4Decompile and CodeGeeX?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LLM4Decompile trust report; CodeGeeX trust report.