--- title: "LLM4Decompile vs code2prompt" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/albertan017-llm4decompile-vs-mufeedvh-code2prompt" tools: ["albertan017-llm4decompile", "mufeedvh-code2prompt"] --- # LLM4Decompile vs code2prompt *GraphCanon updated Aug 17, 2026* ## Verdict Pick LLM4Decompile when lLM4Decompile is primarily Python; code2prompt is Rust; pick code2prompt when code2prompt is primarily Rust; LLM4Decompile is Python. [LLM4Decompile](https://aclanthology.org/2024.emnlp-main.203) reports 7.0k GitHub stars, 546 forks, and 46 open issues, last pushed Feb 12, 2026. [code2prompt](https://code2prompt.dev) has 7.5k stars, 429 forks, and 20 open issues, last pushed Jun 29, 2026. Figures are from public GitHub metadata via [LLM4Decompile's repository](https://github.com/albertan017/LLM4Decompile) and [code2prompt's repository](https://github.com/mufeedvh/code2prompt). | | [LLM4Decompile](/tools/albertan017-llm4decompile.md) | [code2prompt](/tools/mufeedvh-code2prompt.md) | | --- | --- | --- | | Tagline | Decompiling Binary Code with Large Language Models | CLI tool to convert codebase into LLM prompt | | Stars | 6,965 | 7,509 | | Forks | 546 | 429 | | Open issues | 46 | 20 | | Language | Python | Rust | | Adopt for | LLM4Decompile uses large language models to reverse engineer binary code into assembly instructions and potentially source code. | - | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | LLM Frameworks | Developer Tools, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LLM4Decompile](/tools/albertan017-llm4decompile.md) | [code2prompt](/tools/mufeedvh-code2prompt.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Active (82%) | | Days since push | 186d | 28d | | Open issues (now) | 46 | 20 | | Stars delta | +205 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Full report | [trust report](/tools/albertan017-llm4decompile/trust.md) | [trust report](/tools/mufeedvh-code2prompt/trust.md) | ## Decision facts: LLM4Decompile - **Pricing:** freemium - 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. - **Adopt for:** LLM4Decompile uses large language models to reverse engineer binary code into assembly instructions and potentially source code. ## Decision facts: code2prompt - **Hosting:** self hosted - code2prompt operates as a self-hosted CLI tool, allowing for local data processing that is important for users with confidentiality requirements or those who wish to avoid cloud dependency. - **Pricing:** freemium - The code2prompt tool is available under MIT license free of monetary charge. However, premium support or advanced features might incur costs if provided by the development team in future updates. ## Choose when ### Choose LLM4Decompile if… - LLM4Decompile is primarily Python; code2prompt is Rust. - 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. ### Choose code2prompt if… - code2prompt is primarily Rust; LLM4Decompile is Python. - code2prompt operates as a self-hosted CLI tool, allowing for local data processing that is important for users with confidentiality requirements or those who wish to avoid cloud dependency. - Pricing: The code2prompt tool is available under MIT license free of monetary charge. However, premium support or advanced features might incur costs if provided by the development team in future updates.. - Tags unique to code2prompt: ai, chatgpt, claude, cli. - Also covers Developer Tools. - When you aim to structure and deliver your entire codebase into an LLM for comprehensive documentation or refactoring guidance. ## 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. ## When NOT to use code2prompt - In situations requiring real-time interaction or analysis of codebases due to the static nature of its prompt generation process, as this might not cater to agile or evolving project requirements. - If you are in need of a tool beyond simple CLI operation and desire an integrated development environment (IDE) plugin for more interactive and continuous assistance. ## Common questions ### What is the difference between LLM4Decompile and code2prompt? LLM4Decompile: Decompiling Binary Code with Large Language Models. code2prompt: CLI tool to convert codebase into LLM prompt. See the comparison table for live GitHub stats and shared categories. ### When should I choose LLM4Decompile over code2prompt? Choose LLM4Decompile over code2prompt when LLM4Decompile is primarily Python; code2prompt is Rust; 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 code2prompt over LLM4Decompile? Choose code2prompt over LLM4Decompile when code2prompt is primarily Rust; LLM4Decompile is Python; code2prompt operates as a self-hosted CLI tool, allowing for local data processing that is important for users with confidentiality requirements or those who wish to avoid cloud dependency; Pricing: The code2prompt tool is available under MIT license free of monetary charge. However, premium support or advanced features might incur costs if provided by the development team in future updates.; Tags unique to code2prompt: ai, chatgpt, claude, cli; Also covers Developer Tools; When you aim to structure and deliver your entire codebase into an LLM for comprehensive documentation or refactoring guidance. ### 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 code2prompt? In situations requiring real-time interaction or analysis of codebases due to the static nature of its prompt generation process, as this might not cater to agile or evolving project requirements. If you are in need of a tool beyond simple CLI operation and desire an integrated development environment (IDE) plugin for more interactive and continuous assistance. ### Is LLM4Decompile or code2prompt more popular on GitHub? code2prompt has more GitHub stars (7,509 vs 6,965). Stars measure visibility, not whether either tool fits your constraints. ### Are LLM4Decompile and code2prompt open source? Yes - both are open-source projects on GitHub (LLM4Decompile: MIT, code2prompt: MIT). ### Where can I find alternatives to LLM4Decompile or code2prompt? GraphCanon lists graph-backed alternatives at [LLM4Decompile alternatives](/tools/albertan017-llm4decompile/alternatives) and [code2prompt alternatives](/tools/mufeedvh-code2prompt/alternatives) ([LLM4Decompile markdown twin](/tools/albertan017-llm4decompile/alternatives.md), [code2prompt markdown twin](/tools/mufeedvh-code2prompt/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/albertan017-llm4decompile-vs-mufeedvh-code2prompt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LLM4Decompile or code2prompt? LLM4Decompile: Slowing. code2prompt: Active. 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 code2prompt? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LLM4Decompile trust report](/tools/albertan017-llm4decompile/trust); [code2prompt trust report](/tools/mufeedvh-code2prompt/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=albertan017-llm4decompile`](/api/graphcanon/graph?tool=albertan017-llm4decompile) - 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/_