--- title: "DeepSeek-Coder vs codealpaca" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/deepseek-ai-deepseek-coder-vs-sahil280114-codealpaca" tools: ["deepseek-ai-deepseek-coder", "sahil280114-codealpaca"] --- # DeepSeek-Coder vs codealpaca *GraphCanon updated Aug 5, 2026* ## Verdict Pick DeepSeek-Coder if deepSeek-Coder is recognized for its automatic code generation capabilities backed by AI models; pick codealpaca if a specialized LLaMA model for generating code from instructions, leveraging 20K fine-tuning data inspired by the Self-Instruct paper. [DeepSeek-Coder](https://chat.deepseek.com/) reports 24k GitHub stars, 2.9k forks, and 171 open issues, last pushed Nov 11, 2025. [codealpaca](https://github.com/sahil280114/codealpaca) has 1.5k stars, 113 forks, and 17 open issues, last pushed May 12, 2023. Figures are from public GitHub metadata via [DeepSeek-Coder's repository](https://github.com/deepseek-ai/DeepSeek-Coder) and [codealpaca's repository](https://github.com/sahil280114/codealpaca). | | [DeepSeek-Coder](/tools/deepseek-ai-deepseek-coder.md) | [codealpaca](/tools/sahil280114-codealpaca.md) | | --- | --- | --- | | Tagline | DeepSeek Coder enables automatic code generation using AI. | An instruction-following LLaMA model for code generation. | | Stars | 24,043 | 1,514 | | Forks | 2,903 | 113 | | Open issues | 171 | 17 | | Language | Python | Python | | Adopt for | DeepSeek-Coder is recognized for its automatic code generation capabilities backed by AI models. | A specialized LLaMA model for generating code from instructions, leveraging 20K fine-tuning data inspired by the Self-Instruct paper. | | Persona | - | - | | Runtime | - | - | | License | MIT | The project uses Apache-2.0 license, allowing users to utilize the source code and documentation freely. | | Categories | Developer Tools, LLM Frameworks | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [DeepSeek-Coder](/tools/deepseek-ai-deepseek-coder.md) | [codealpaca](/tools/sahil280114-codealpaca.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Dormant (18%) | | Days since push | 267d | 1180d | | Open issues (now) | 171 | 17 | | Owner type | Organization | User | | Full report | [trust report](/tools/deepseek-ai-deepseek-coder/trust.md) | [trust report](/tools/sahil280114-codealpaca/trust.md) | ## Decision facts: DeepSeek-Coder - **Adopt for:** DeepSeek-Coder is recognized for its automatic code generation capabilities backed by AI models. ## Decision facts: codealpaca - **Requirements:** Model weights are not available in this repository due to licensing restrictions. - **Adopt for:** A specialized LLaMA model for generating code from instructions, leveraging 20K fine-tuning data inspired by the Self-Instruct paper. - **License detail:** The project uses Apache-2.0 license, allowing users to utilize the source code and documentation freely. ## Choose when ### Choose DeepSeek-Coder if… - License: DeepSeek-Coder is MIT, codealpaca is Apache-2.0. - Tags unique to DeepSeek-Coder: commercial use allowed, mit-license. - Also covers Developer Tools. - - When you require an assist in writing Python scripts that are repetitive and well-defined ### Choose codealpaca if… - License: codealpaca is Apache-2.0, DeepSeek-Coder is MIT. - Requirements: Model weights are not available in this repository due to licensing restrictions.. - Tags unique to codealpaca: fine-tuning, instruction-following, python. - Also covers Model Training. - When you need instruction-following capabilities tailored specifically for code generation tasks. ## 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 ## When NOT to use codealpaca - Avoid if you require models fine-tuned on datasets that cover a broader spectrum of non-code-related instructions beyond code editing and generation. - Do not use this tool when you must adhere to strict compliance or safety standards for model output, as the Code Alpaca model is noted to be unsafe and not fine-tuned for harmlessness. ## Common questions ### What is the difference between DeepSeek-Coder and codealpaca? DeepSeek-Coder: DeepSeek Coder enables automatic code generation using AI.. codealpaca: An instruction-following LLaMA model for code generation.. See the comparison table for live GitHub stats and shared categories. ### When should I choose DeepSeek-Coder over codealpaca? Choose DeepSeek-Coder over codealpaca when License: DeepSeek-Coder is MIT, codealpaca is Apache-2.0; Tags unique to DeepSeek-Coder: 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 choose codealpaca over DeepSeek-Coder? Choose codealpaca over DeepSeek-Coder when License: codealpaca is Apache-2.0, DeepSeek-Coder is MIT; Requirements: Model weights are not available in this repository due to licensing restrictions.; Tags unique to codealpaca: fine-tuning, instruction-following, python; Also covers Model Training; When you need instruction-following capabilities tailored specifically for code generation tasks. ### 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 ### When should I avoid codealpaca? Avoid if you require models fine-tuned on datasets that cover a broader spectrum of non-code-related instructions beyond code editing and generation. Do not use this tool when you must adhere to strict compliance or safety standards for model output, as the Code Alpaca model is noted to be unsafe and not fine-tuned for harmlessness. ### Is DeepSeek-Coder or codealpaca more popular on GitHub? DeepSeek-Coder has more GitHub stars (24,043 vs 1,514). Stars measure visibility, not whether either tool fits your constraints. ### Are DeepSeek-Coder and codealpaca open source? Yes - both are open-source projects on GitHub (DeepSeek-Coder: MIT, codealpaca: Apache-2.0). ### Where can I find alternatives to DeepSeek-Coder or codealpaca? GraphCanon lists graph-backed alternatives at [DeepSeek-Coder alternatives](/tools/deepseek-ai-deepseek-coder/alternatives) and [codealpaca alternatives](/tools/sahil280114-codealpaca/alternatives) ([DeepSeek-Coder markdown twin](/tools/deepseek-ai-deepseek-coder/alternatives.md), [codealpaca markdown twin](/tools/sahil280114-codealpaca/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/deepseek-ai-deepseek-coder-vs-sahil280114-codealpaca.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, DeepSeek-Coder or codealpaca? DeepSeek-Coder: Slowing. codealpaca: 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 DeepSeek-Coder and codealpaca? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [DeepSeek-Coder trust report](/tools/deepseek-ai-deepseek-coder/trust); [codealpaca trust report](/tools/sahil280114-codealpaca/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=deepseek-ai-deepseek-coder`](/api/graphcanon/graph?tool=deepseek-ai-deepseek-coder) - 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/_