--- title: "LLM4Decompile vs DeepSeek-Coder" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/albertan017-llm4decompile-vs-deepseek-ai-deepseek-coder" tools: ["albertan017-llm4decompile", "deepseek-ai-deepseek-coder"] --- # LLM4Decompile vs DeepSeek-Coder *GraphCanon updated Aug 17, 2026* ## Verdict Pick LLM4Decompile if lLM4Decompile uses large language models to reverse engineer binary code into assembly instructions and potentially source code; pick DeepSeek-Coder if deepSeek-Coder is recognized for its automatic code generation capabilities backed by AI models. [LLM4Decompile](https://aclanthology.org/2024.emnlp-main.203) reports 7.0k GitHub stars, 546 forks, and 46 open issues, last pushed Feb 12, 2026. [DeepSeek-Coder](https://chat.deepseek.com/) has 24k stars, 2.9k forks, and 171 open issues, last pushed Nov 11, 2025. Figures are from public GitHub metadata via [LLM4Decompile's repository](https://github.com/albertan017/LLM4Decompile) and [DeepSeek-Coder's repository](https://github.com/deepseek-ai/DeepSeek-Coder). | | [LLM4Decompile](/tools/albertan017-llm4decompile.md) | [DeepSeek-Coder](/tools/deepseek-ai-deepseek-coder.md) | | --- | --- | --- | | Tagline | Decompiling Binary Code with Large Language Models | DeepSeek Coder enables automatic code generation using AI. | | Stars | 6,965 | 24,043 | | Forks | 546 | 2,903 | | Open issues | 46 | 171 | | Language | Python | Python | | Adopt for | LLM4Decompile uses large language models to reverse engineer binary code into assembly instructions and potentially source code. | DeepSeek-Coder is recognized for its automatic code generation capabilities backed by AI models. | | 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) | [DeepSeek-Coder](/tools/deepseek-ai-deepseek-coder.md) | | --- | --- | --- | | Days since push | 186d | 267d | | Open issues (now) | 46 | 171 | | Stars delta | +205 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Owner type | User | Organization | | Full report | [trust report](/tools/albertan017-llm4decompile/trust.md) | [trust report](/tools/deepseek-ai-deepseek-coder/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: DeepSeek-Coder - **Adopt for:** DeepSeek-Coder is recognized for its automatic code generation capabilities backed by AI models. ## Choose when ### 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. ### Choose DeepSeek-Coder if… - Tags unique to DeepSeek-Coder: code generation, commercial use allowed, mit-license. - Also covers Developer Tools. - - When you require an assist in writing Python scripts that are repetitive and well-defined ## 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 DeepSeek-Coder - - When your project involves languages other than Python, given DeepSeek-Coder specifically serves Python programming - - If you need granular control over every line of code being generated; DeepSeek-Coder is best for generating well-defined chunks of code not bespoke individual lines ## Common questions ### What is the difference between LLM4Decompile and DeepSeek-Coder? LLM4Decompile: Decompiling Binary Code with Large Language Models. DeepSeek-Coder: DeepSeek Coder enables automatic code generation using AI.. See the comparison table for live GitHub stats and shared categories. ### When should I choose LLM4Decompile over DeepSeek-Coder? Choose LLM4Decompile over DeepSeek-Coder 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 DeepSeek-Coder over LLM4Decompile? Choose DeepSeek-Coder over LLM4Decompile when Tags unique to DeepSeek-Coder: code generation, commercial use allowed, mit-license; Also covers Developer Tools; - When you require an assist in writing Python scripts that are repetitive and well-defined. ### 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 DeepSeek-Coder? - When your project involves languages other than Python, given DeepSeek-Coder specifically serves Python programming - If you need granular control over every line of code being generated; DeepSeek-Coder is best for generating well-defined chunks of code not bespoke individual lines ### Is LLM4Decompile or DeepSeek-Coder more popular on GitHub? DeepSeek-Coder has more GitHub stars (24,043 vs 6,965). Stars measure visibility, not whether either tool fits your constraints. ### Are LLM4Decompile and DeepSeek-Coder open source? Yes - both are open-source projects on GitHub (LLM4Decompile: MIT, DeepSeek-Coder: MIT). ### Where can I find alternatives to LLM4Decompile or DeepSeek-Coder? GraphCanon lists graph-backed alternatives at [LLM4Decompile alternatives](/tools/albertan017-llm4decompile/alternatives) and [DeepSeek-Coder alternatives](/tools/deepseek-ai-deepseek-coder/alternatives) ([LLM4Decompile markdown twin](/tools/albertan017-llm4decompile/alternatives.md), [DeepSeek-Coder markdown twin](/tools/deepseek-ai-deepseek-coder/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-deepseek-ai-deepseek-coder.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LLM4Decompile or DeepSeek-Coder? LLM4Decompile: Slowing. DeepSeek-Coder: Slowing. 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 DeepSeek-Coder? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LLM4Decompile trust report](/tools/albertan017-llm4decompile/trust); [DeepSeek-Coder trust report](/tools/deepseek-ai-deepseek-coder/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/_