--- title: "LLMSys-PaperList vs litellm" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/amberljc-llmsys-paperlist-vs-berriai-litellm" tools: ["amberljc-llmsys-paperlist", "berriai-litellm"] --- # LLMSys-PaperList vs litellm *GraphCanon updated Jul 11, 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 litellm if litellm is a Python SDK and Proxy Server that facilitates the interaction with over 100 LLM APIs, offering features such as cost tracking, guardrails, load balancing, and logging. [LLMSys-PaperList](https://github.com/AmberLJC/LLMSys-PaperList) reports 2.2k GitHub stars, 114 forks, and 0 open issues, last pushed Jul 9, 2026. [litellm](https://docs.litellm.ai/docs/) has 53k stars, 9.7k forks, and 3.9k open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [LLMSys-PaperList's repository](https://github.com/AmberLJC/LLMSys-PaperList) and [litellm's repository](https://github.com/BerriAI/litellm). | | [LLMSys-PaperList](/tools/amberljc-llmsys-paperlist.md) | [litellm](/tools/berriai-litellm.md) | | --- | --- | --- | | Tagline | Curated list of academic papers related to Large Language Model systems | Python SDK and Proxy Server for calling multiple LLM APIs | | Stars | 2,175 | 53,271 | | Forks | 114 | 9,671 | | Open issues | 0 | 3,915 | | Language | - | Python | | Adopt for | LLMSys-PaperList offers a comprehensive list of papers and resources tailored specifically to Large Language Model (LLM) systems. | litellm is a Python SDK and Proxy Server that facilitates the interaction with over 100 LLM APIs, offering features such as cost tracking, guardrails, load balancing, and logging. | | Persona | - | - | | Runtime | - | - | | License | (unknown) | The licensing terms for LiteLLM are provided under a license type categorized as 'Other'; details of the exact license should be referenced directly from its source. | | Categories | Inference & Serving, LLM Frameworks, Model Training | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LLMSys-PaperList](/tools/amberljc-llmsys-paperlist.md) | [litellm](/tools/berriai-litellm.md) | | --- | --- | --- | | Days since push | 1d | 0d | | Open issues (now) | 0 | 3.9k | | Owner type | User | Organization | | Security scan | No lockfile | 2 low (2 low) | | Full report | [trust report](/tools/amberljc-llmsys-paperlist/trust.md) | [trust report](/tools/berriai-litellm/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: litellm - **Pricing:** freemium - While the core functionality is provided free, specific extended features might require a paid plan. - **Requirements:** Requires Docker - **Adopt for:** litellm is a Python SDK and Proxy Server that facilitates the interaction with over 100 LLM APIs, offering features such as cost tracking, guardrails, load balancing, and logging. - **License detail:** The licensing terms for LiteLLM are provided under a license type categorized as 'Other'; details of the exact license should be referenced directly from its source. ## 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 Model Training. - - When you need a curated list focusing on technical advancements in pre-training, post-training, serving, and multi-modal LLM systems. ### Choose litellm if… - Pricing: While the core functionality is provided free, specific extended features might require a paid plan.. - Requirements: Requires Docker. - Tags unique to litellm: ai-gateway, azure-openai, bedrock, llm. - litellm ships Docker support for self-hosted deployment. - When you need to integrate multiple LLM (Language Learning Modelling) APIs into your application across different providers like Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, Hugging ## 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 litellm - If your project only requires interaction with a single LLM API and basic functionalities, litellm may be overkill. ## Common questions ### What is the difference between LLMSys-PaperList and litellm? LLMSys-PaperList: Curated list of academic papers related to Large Language Model systems. litellm: Python SDK and Proxy Server for calling multiple LLM APIs. See the comparison table for live GitHub stats and shared categories. ### When should I choose LLMSys-PaperList over litellm? Choose LLMSys-PaperList over litellm when (repository does not specify hosting environment); Tags unique to LLMSys-PaperList: academic-sources, framework-overview, inference-techniques, research papers; Also covers Model Training; - 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 litellm over LLMSys-PaperList? Choose litellm over LLMSys-PaperList when Pricing: While the core functionality is provided free, specific extended features might require a paid plan.; Requirements: Requires Docker; Tags unique to litellm: ai-gateway, azure-openai, bedrock, llm; litellm ships Docker support for self-hosted deployment; When you need to integrate multiple LLM (Language Learning Modelling) APIs into your application across different providers like Bedrock, Azure, OpenAI, VertexAI, Cohere, Anthropic, Sagemaker, Hugging. ### 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 litellm? If your project only requires interaction with a single LLM API and basic functionalities, litellm may be overkill. ### Is LLMSys-PaperList or litellm more popular on GitHub? litellm has more GitHub stars (53,271 vs 2,175). Stars measure visibility, not whether either tool fits your constraints. ### Are LLMSys-PaperList and litellm open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to LLMSys-PaperList or litellm? GraphCanon lists graph-backed alternatives at [LLMSys-PaperList alternatives](/tools/amberljc-llmsys-paperlist/alternatives) and [litellm alternatives](/tools/berriai-litellm/alternatives) ([LLMSys-PaperList markdown twin](/tools/amberljc-llmsys-paperlist/alternatives.md), [litellm markdown twin](/tools/berriai-litellm/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-berriai-litellm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LLMSys-PaperList or litellm? LLMSys-PaperList: Very active. litellm: Very 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 LLMSys-PaperList and litellm? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LLMSys-PaperList trust report](/tools/amberljc-llmsys-paperlist/trust); [litellm trust report](/tools/berriai-litellm/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/_