--- title: "awesome-gpt vs awesome-LLM-resources" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/formulahendry-awesome-gpt-vs-wangrongsheng-awesome-llm-resources" tools: ["formulahendry-awesome-gpt", "wangrongsheng-awesome-llm-resources"] --- # awesome-gpt vs awesome-LLM-resources *GraphCanon updated Aug 17, 2026* ## Verdict Pick awesome-gpt if awesome-gpt is a curated list of GPT and related resources, serving as a reference for developers exploring or working with large language models and their applications; pick awesome-LLM-resources if awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as. [awesome-gpt](https://github.com/formulahendry/awesome-gpt) reports 1.0k GitHub stars, 75 forks, and 27 open issues, last pushed May 29, 2024. [awesome-LLM-resources](https://github.com/WangRongsheng/awesome-LLM-resources) has 8.8k stars, 950 forks, and 23 open issues, last pushed Aug 14, 2026. Figures are from public GitHub metadata via [awesome-gpt's repository](https://github.com/formulahendry/awesome-gpt) and [awesome-LLM-resources's repository](https://github.com/WangRongsheng/awesome-LLM-resources). | | [awesome-gpt](/tools/formulahendry-awesome-gpt.md) | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) | | --- | --- | --- | | Tagline | Curated list of GPT and related resources | Summary of the world's best LLM resources. | | Stars | 1,043 | 8,845 | | Forks | 75 | 950 | | Open issues | 27 | 23 | | Language | - | - | | Adopt for | awesome-gpt is a curated list of GPT and related resources, serving as a reference for developers exploring or working with large language models and their applications. | awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as a | | Persona | - | - | | Runtime | - | - | | License | - | Apache-2.0 | | Categories | Developer Tools, LLM Frameworks | AI Agents, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-gpt](/tools/formulahendry-awesome-gpt.md) | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 799d | 2d | | Open issues (now) | 27 | 23 | | Stars delta | Unknown | +142 (30d) | | Open issues delta | Unknown | -13 (30d) | | Full report | [trust report](/tools/formulahendry-awesome-gpt/trust.md) | [trust report](/tools/wangrongsheng-awesome-llm-resources/trust.md) | ## Decision facts: awesome-gpt - **Pricing:** unknown - Information about pricing is unavailable and likely does not apply as this is a curated list rather than a software service with licensing costs. - **Requirements:** Since awesome-gpt is an informational repository, it itself does not have RAM requirements or Docker needs. However, users might require internet access to view - **Adopt for:** awesome-gpt is a curated list of GPT and related resources, serving as a reference for developers exploring or working with large language models and their applications. ## Decision facts: awesome-LLM-resources - **Adopt for:** awesome-LLM-resources offers a curated and comprehensive list of resources related to Large Language Models (LLMs), including materials for specialized areas like RAG (Retrieval-Augmented Generation) and agentic RL, as a ## Choose when ### Choose awesome-gpt if… - Pricing: Information about pricing is unavailable and likely does not apply as this is a curated list rather than a software service with licensing costs.. - Requirements: Since awesome-gpt is an informational repository, it itself does not have RAM requirements or Docker needs. However, users might require internet access to view. - Tags unique to awesome-gpt: chatgpt, gpt. - Use awesome-gpt if you are looking for a comprehensive collection of links and resources specifically focused on GPT, ChatGPT, OpenAI products, and other large-scale AI tools. ### Choose awesome-LLM-resources if… - Tags unique to awesome-LLM-resources: awesome-list, book, course, large language models. - Also covers AI Agents, Evaluation & Observability, Inference & Serving, Model Training. - - It's ideal when you seek an exhaustive and up-to-date compilation covering extensive knowledge points in LLM technologies. ## When NOT to use awesome-gpt - Avoid using awesome-gpt if you need detailed tutorials or in-depth technical documentation, as it primarily functions as an index of resources rather than an educational material provider. - Do not rely on awesome-gpt for real-time updates or specific usage statistics, tool availability, or pricing plans since the repository relies heavily on links external to its curation. ## When NOT to use awesome-LLM-resources - - Avoid using this resource if you specifically need detailed step-by-step guides or hands-on tutorials that focus deeply on a single technology rather than broad coverage. - - It might not be the best choice when you are looking for resources in languages other than English, especially given its extensive English content. ## Common questions ### What is the difference between awesome-gpt and awesome-LLM-resources? awesome-gpt: Curated list of GPT and related resources. awesome-LLM-resources: Summary of the world's best LLM resources.. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-gpt over awesome-LLM-resources? Choose awesome-gpt over awesome-LLM-resources when Pricing: Information about pricing is unavailable and likely does not apply as this is a curated list rather than a software service with licensing costs.; Requirements: Since awesome-gpt is an informational repository, it itself does not have RAM requirements or Docker needs. However, users might require internet access to view; Tags unique to awesome-gpt: chatgpt, gpt; Use awesome-gpt if you are looking for a comprehensive collection of links and resources specifically focused on GPT, ChatGPT, OpenAI products, and other large-scale AI tools. ### When should I choose awesome-LLM-resources over awesome-gpt? Choose awesome-LLM-resources over awesome-gpt when Tags unique to awesome-LLM-resources: awesome-list, book, course, large language models; Also covers AI Agents, Evaluation & Observability, Inference & Serving, Model Training; - It's ideal when you seek an exhaustive and up-to-date compilation covering extensive knowledge points in LLM technologies. ### When should I avoid awesome-gpt? Avoid using awesome-gpt if you need detailed tutorials or in-depth technical documentation, as it primarily functions as an index of resources rather than an educational material provider. Do not rely on awesome-gpt for real-time updates or specific usage statistics, tool availability, or pricing plans since the repository relies heavily on links external to its curation. ### When should I avoid awesome-LLM-resources? - Avoid using this resource if you specifically need detailed step-by-step guides or hands-on tutorials that focus deeply on a single technology rather than broad coverage. - It might not be the best choice when you are looking for resources in languages other than English, especially given its extensive English content. ### Is awesome-gpt or awesome-LLM-resources more popular on GitHub? awesome-LLM-resources has more GitHub stars (8,845 vs 1,043). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-gpt and awesome-LLM-resources open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to awesome-gpt or awesome-LLM-resources? GraphCanon lists graph-backed alternatives at [awesome-gpt alternatives](/tools/formulahendry-awesome-gpt/alternatives) and [awesome-LLM-resources alternatives](/tools/wangrongsheng-awesome-llm-resources/alternatives) ([awesome-gpt markdown twin](/tools/formulahendry-awesome-gpt/alternatives.md), [awesome-LLM-resources markdown twin](/tools/wangrongsheng-awesome-llm-resources/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/formulahendry-awesome-gpt-vs-wangrongsheng-awesome-llm-resources.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-gpt or awesome-LLM-resources? awesome-gpt: Dormant. awesome-LLM-resources: 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 awesome-gpt and awesome-LLM-resources? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-gpt trust report](/tools/formulahendry-awesome-gpt/trust); [awesome-LLM-resources trust report](/tools/wangrongsheng-awesome-llm-resources/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=formulahendry-awesome-gpt`](/api/graphcanon/graph?tool=formulahendry-awesome-gpt) - 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/_