Comparison
LLM4Decompile vs HLCE
Verdict
Pick LLM4Decompile if lLM4Decompile uses large language models to reverse engineer binary code into assembly instructions and potentially source code; pick HLCE if hLCE offers evaluation scripts to assess code generation using LLMs, specifically for research purposes.
Markdown twin · LLM4Decompile alternatives · HLCE alternatives
GraphCanon updated Sep 20, 2026
6views this month
vs
Trust & integrity
| Signal | LLM4Decompile | HLCE |
|---|---|---|
| Maintenance | Slowing (186d since push) As of Aug 17, 2026 · github_public_v1 | Dormant (383d since push) As of Sep 8, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Aug 17, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 8, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 11, 2026 · osv@v1 | Published findings As of Jul 15, 2026 · 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
- HLCE
- Source Evaluation scripts for Humanity's Last Code Exam
Stars
- LLM4Decompile
- 7.0k
- HLCE
- 96
Forks
- LLM4Decompile
- 546
- HLCE
- 8
Open issues
- LLM4Decompile
- 46
- HLCE
- 1
Language
- LLM4Decompile
- Python
- HLCE
- Python
Adopt for
- LLM4Decompile
- LLM4Decompile uses large language models to reverse engineer binary code into assembly instructions and potentially source code.
- HLCE
- HLCE offers evaluation scripts to assess code generation using LLMs, specifically for research purposes.
Persona
- LLM4Decompile
- -
- HLCE
- -
Runtime
- LLM4Decompile
- -
- HLCE
- -
License
- LLM4Decompile
- MIT
- HLCE
- -
Last pushed
- LLM4Decompile
- Feb 12, 2026
- HLCE
- Aug 21, 2025
Categories
- LLM4Decompile
- LLM Frameworks
- HLCE
- Evaluation & Observability, LLM Frameworks
Trust and health
Maintenance
- LLM4Decompile
- Slowing (36%)
- HLCE
- Dormant (18%)
Days since push
- LLM4Decompile
- 186d
- HLCE
- 383d
Open issues (now)
- LLM4Decompile
- 46
- HLCE
- 1
Stars delta
- LLM4Decompile
- +205 (30d)
- HLCE
- 0 (30d)
Owner type
- LLM4Decompile
- User
- HLCE
- Organization
Full report
- LLM4Decompile
- Trust report
- HLCE
- Trust report
Choose LLM4Decompile if…
- 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 HLCE if…
- Tags unique to HLCE: benchmark, codegen, codellm, llm-evaluation.
- Also covers Evaluation & Observability.
- 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 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.
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 Sep 20, 2026
- GitHub forks (albertan017/LLM4Decompile) · observed Sep 20, 2026
- Last push (albertan017/LLM4Decompile) · observed Feb 12, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Humanity-s-Last-Code-Exam/HLCE) · observed Sep 20, 2026
- GitHub forks (Humanity-s-Last-Code-Exam/HLCE) · observed Sep 20, 2026
- Last push (Humanity-s-Last-Code-Exam/HLCE) · observed Aug 21, 2025
- License file (unknown) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: LLM4Decompile 7.0k · HLCE 96 (synced Sep 20, 2026).
Common questions
- What is the difference between LLM4Decompile and HLCE?
- LLM4Decompile: Decompiling Binary Code with Large 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 LLM4Decompile over HLCE?
- Choose LLM4Decompile over HLCE when 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 HLCE over LLM4Decompile?
- Choose HLCE over LLM4Decompile when Tags unique to HLCE: benchmark, codegen, codellm, llm-evaluation; Also covers Evaluation & Observability; 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 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 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 LLM4Decompile or HLCE more popular on GitHub?
- LLM4Decompile has more GitHub stars (6,965 vs 96). Stars measure visibility, not whether either tool fits your constraints.
- Are LLM4Decompile and HLCE open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to LLM4Decompile or HLCE?
- GraphCanon lists graph-backed alternatives at LLM4Decompile alternatives and HLCE alternatives (LLM4Decompile markdown twin, HLCE 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 HLCE?
- LLM4Decompile: Slowing. HLCE: 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 HLCE?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LLM4Decompile trust report; HLCE trust report.