--- title: "LLMSys-PaperList vs DeepSeek-R1" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/amberljc-llmsys-paperlist-vs-deepseek-ai-deepseek-r1" tools: ["amberljc-llmsys-paperlist", "deepseek-ai-deepseek-r1"] --- # LLMSys-PaperList vs DeepSeek-R1 *GraphCanon updated Jul 12, 2026* ## Verdict Pick LLMSys-PaperList if lLMSys-PaperList offers a comprehensive list of papers and resources tailored specifically to Large Language Model (LLM) systems; pick DeepSeek-R1 if deepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use. [LLMSys-PaperList](https://github.com/AmberLJC/LLMSys-PaperList) reports 2.2k GitHub stars, 114 forks, and 0 open issues, last pushed Jul 9, 2026. [DeepSeek-R1](https://github.com/deepseek-ai/DeepSeek-R1) has 92k stars, 12k forks, and 45 open issues, last pushed Jun 27, 2025. Figures are from public GitHub metadata via [LLMSys-PaperList's repository](https://github.com/AmberLJC/LLMSys-PaperList) and [DeepSeek-R1's repository](https://github.com/deepseek-ai/DeepSeek-R1). | | [LLMSys-PaperList](/tools/amberljc-llmsys-paperlist.md) | [DeepSeek-R1](/tools/deepseek-ai-deepseek-r1.md) | | --- | --- | --- | | Tagline | Curated list of academic papers related to Large Language Model systems | Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses. | | Stars | 2,175 | 91,991 | | Forks | 114 | 11,711 | | Open issues | 0 | 45 | | Language | - | - | | Adopt for | LLMSys-PaperList offers a comprehensive list of papers and resources tailored specifically to Large Language Model (LLM) systems. | DeepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use. | | Persona | - | - | | Runtime | - | - | | License | (unknown) | MIT | | Categories | Inference & Serving, LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LLMSys-PaperList](/tools/amberljc-llmsys-paperlist.md) | [DeepSeek-R1](/tools/deepseek-ai-deepseek-r1.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 1d | 379d | | Open issues (now) | 0 | 45 | | Owner type | User | Organization | | Full report | [trust report](/tools/amberljc-llmsys-paperlist/trust.md) | [trust report](/tools/deepseek-ai-deepseek-r1/trust.md) | ## Decision facts: LLMSys-PaperList - **Hosting:** unknown - (repository does not specify hosting environment) - **Adopt for:** LLMSys-PaperList offers a comprehensive list of papers and resources tailored specifically to Large Language Model (LLM) systems. - **License detail:** (unknown) ## Decision facts: DeepSeek-R1 - **Pricing:** freemium - The repository allows for commercial use under the MIT License or respective original licenses with no explicit monetary costs outlined in the repository. - **Requirements:** Min 4 GB RAM; This is a rough estimate based on common model requirements. Specific models within DeepSeek-R1 may have different resource needs. - **Adopt for:** DeepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use. ## Choose when ### Choose LLMSys-PaperList if… - (repository does not specify hosting environment) - Tags unique to LLMSys-PaperList: academic-sources, framework-overview, inference-techniques, research papers. - Also covers Inference & Serving. - - When you need a curated list focusing on technical advancements in pre-training, post-training, serving, and multi-modal LLM systems. ### Choose DeepSeek-R1 if… - Pricing: The repository allows for commercial use under the MIT License or respective original licenses with no explicit monetary costs outlined in the repository.. - Requirements: Min 4 GB RAM; This is a rough estimate based on common model requirements. Specific models within DeepSeek-R1 may have different resource needs.. - Tags unique to DeepSeek-R1: commercial use, derived models, distilled models, mit license. - When you need to work with pre-trained models derived specifically from the Qwen-2.5 and Llama3.x series, benefiting from their unique characteristics. ## When NOT to use LLMSys-PaperList - - If you are looking for a general repository of machine learning papers rather than specific developments related to Large Language Models. - - When your primary need is documentation or code examples rather than academic papers and project insights. - - For applications where real-time updates and active community support are imperative, as LLMSys-PaperList primarily serves as a static list without user interaction features like commenting or liveＱ ## When NOT to use DeepSeek-R1 - Avoid if you need foundational models rather than distilled versions, as DeepSeek-R1 specializes in providing smaller, more efficient models suitable for resource-constrained environments. - If your project is tightly regulated or requires models from a different lineage, as DeepSeek-R1 exclusively provides derivatives of Qwen and LLaMA series. ## Common questions ### What is the difference between LLMSys-PaperList and DeepSeek-R1? LLMSys-PaperList: Curated list of academic papers related to Large Language Model systems. DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. See the comparison table for live GitHub stats and shared categories. ### When should I choose LLMSys-PaperList over DeepSeek-R1? Choose LLMSys-PaperList over DeepSeek-R1 when (repository does not specify hosting environment); Tags unique to LLMSys-PaperList: academic-sources, framework-overview, inference-techniques, research papers; Also covers Inference & Serving; - When you need a curated list focusing on technical advancements in pre-training, post-training, serving, and multi-modal LLM systems. ### When should I choose DeepSeek-R1 over LLMSys-PaperList? Choose DeepSeek-R1 over LLMSys-PaperList when Pricing: The repository allows for commercial use under the MIT License or respective original licenses with no explicit monetary costs outlined in the repository.; Requirements: Min 4 GB RAM; This is a rough estimate based on common model requirements. Specific models within DeepSeek-R1 may have different resource needs.; Tags unique to DeepSeek-R1: commercial use, derived models, distilled models, mit license; When you need to work with pre-trained models derived specifically from the Qwen-2.5 and Llama3.x series, benefiting from their unique characteristics. ### When should I avoid LLMSys-PaperList? - If you are looking for a general repository of machine learning papers rather than specific developments related to Large Language Models. - When your primary need is documentation or code examples rather than academic papers and project insights. - For applications where real-time updates and active community support are imperative, as LLMSys-PaperList primarily serves as a static list without user interaction features like commenting or liveＱ ### When should I avoid DeepSeek-R1? Avoid if you need foundational models rather than distilled versions, as DeepSeek-R1 specializes in providing smaller, more efficient models suitable for resource-constrained environments. If your project is tightly regulated or requires models from a different lineage, as DeepSeek-R1 exclusively provides derivatives of Qwen and LLaMA series. ### Is LLMSys-PaperList or DeepSeek-R1 more popular on GitHub? DeepSeek-R1 has more GitHub stars (91,991 vs 2,175). Stars measure visibility, not whether either tool fits your constraints. ### Are LLMSys-PaperList and DeepSeek-R1 open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to LLMSys-PaperList or DeepSeek-R1? GraphCanon lists graph-backed alternatives at [LLMSys-PaperList alternatives](/tools/amberljc-llmsys-paperlist/alternatives) and [DeepSeek-R1 alternatives](/tools/deepseek-ai-deepseek-r1/alternatives) ([LLMSys-PaperList markdown twin](/tools/amberljc-llmsys-paperlist/alternatives.md), [DeepSeek-R1 markdown twin](/tools/deepseek-ai-deepseek-r1/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/amberljc-llmsys-paperlist-vs-deepseek-ai-deepseek-r1.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LLMSys-PaperList or DeepSeek-R1? LLMSys-PaperList: Very active. DeepSeek-R1: 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 LLMSys-PaperList and DeepSeek-R1? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LLMSys-PaperList trust report](/tools/amberljc-llmsys-paperlist/trust); [DeepSeek-R1 trust report](/tools/deepseek-ai-deepseek-r1/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=amberljc-llmsys-paperlist`](/api/graphcanon/graph?tool=amberljc-llmsys-paperlist) - 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/_