--- title: "awesome-LLM-resources vs GLM-130B" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/wangrongsheng-awesome-llm-resources-vs-zai-org-glm-130b" tools: ["wangrongsheng-awesome-llm-resources", "zai-org-glm-130b"] --- # awesome-LLM-resources vs GLM-130B *GraphCanon updated Aug 17, 2026* ## Verdict 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 a; pick GLM-130B if gLM-130B specializes in bilingual capabilities and is open source under the Apache-2.0 license. [awesome-LLM-resources](https://github.com/WangRongsheng/awesome-LLM-resources) reports 8.8k GitHub stars, 950 forks, and 23 open issues, last pushed Aug 14, 2026. [GLM-130B](https://github.com/zai-org/GLM-130B) has 7.7k stars, 600 forks, and 124 open issues, last pushed Jul 25, 2023. Figures are from public GitHub metadata via [awesome-LLM-resources's repository](https://github.com/WangRongsheng/awesome-LLM-resources) and [GLM-130B's repository](https://github.com/zai-org/GLM-130B). | | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) | [GLM-130B](/tools/zai-org-glm-130b.md) | | --- | --- | --- | | Tagline | Summary of the world's best LLM resources. | GLM-130B: An Open Bilingual Pre-Trained Model | | Stars | 8,845 | 7,656 | | Forks | 950 | 600 | | Open issues | 23 | 124 | | Language | - | Python | | 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 | GLM-130B specializes in bilingual capabilities and is open source under the Apache-2.0 license. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | The GLM-130B codebase and framework are available under the permissive Apache-2.0 license; however, usage of model weights is governed by its own Model License. | | Categories | AI Agents, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) | [GLM-130B](/tools/zai-org-glm-130b.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 2d | 1103d | | Open issues (now) | 23 | 124 | | Stars delta | +142 (30d) | Unknown | | Open issues delta | -13 (30d) | Unknown | | Owner type | User | Organization | | Full report | [trust report](/tools/wangrongsheng-awesome-llm-resources/trust.md) | [trust report](/tools/zai-org-glm-130b/trust.md) | ## 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 ## Decision facts: GLM-130B - **Pricing:** freemium - Free to use with specific licensing requirements for model weights. - **Requirements:** Min 8 GB RAM - **Adopt for:** GLM-130B specializes in bilingual capabilities and is open source under the Apache-2.0 license. - **License detail:** The GLM-130B codebase and framework are available under the permissive Apache-2.0 license; however, usage of model weights is governed by its own Model License. ## Choose when ### Choose awesome-LLM-resources if… - Tags unique to awesome-LLM-resources: awesome-list, book, course, large language models. - Also covers AI Agents, Developer Tools, Evaluation & Observability, Inference & Serving. - - It's ideal when you seek an exhaustive and up-to-date compilation covering extensive knowledge points in LLM technologies. ### Choose GLM-130B if… - Pricing: Free to use with specific licensing requirements for model weights.. - Requirements: Min 8 GB RAM. - Tags unique to GLM-130B: bilingual, iclr 2023, language-model, pre-trained. - Use GLM-130B when you need strong support for two languages to facilitate multilingual content creation or processing, given its specialized training in bilingual contexts. ## 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. ## When NOT to use GLM-130B - Avoid GLM-130B if your application demands single-language proficiency exclusively, as its strength lies specifically in bilingual support. - Do not use this model if you seek a resource with multilingual capabilities beyond two specific languages, since it focuses particularly on only a dual-language environment. ## Common questions ### What is the difference between awesome-LLM-resources and GLM-130B? awesome-LLM-resources: Summary of the world's best LLM resources.. GLM-130B: GLM-130B: An Open Bilingual Pre-Trained Model. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-LLM-resources over GLM-130B? Choose awesome-LLM-resources over GLM-130B when Tags unique to awesome-LLM-resources: awesome-list, book, course, large language models; Also covers AI Agents, Developer Tools, Evaluation & Observability, Inference & Serving; - It's ideal when you seek an exhaustive and up-to-date compilation covering extensive knowledge points in LLM technologies. ### When should I choose GLM-130B over awesome-LLM-resources? Choose GLM-130B over awesome-LLM-resources when Pricing: Free to use with specific licensing requirements for model weights.; Requirements: Min 8 GB RAM; Tags unique to GLM-130B: bilingual, iclr 2023, language-model, pre-trained; Use GLM-130B when you need strong support for two languages to facilitate multilingual content creation or processing, given its specialized training in bilingual contexts. ### 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. ### When should I avoid GLM-130B? Avoid GLM-130B if your application demands single-language proficiency exclusively, as its strength lies specifically in bilingual support. Do not use this model if you seek a resource with multilingual capabilities beyond two specific languages, since it focuses particularly on only a dual-language environment. ### Is awesome-LLM-resources or GLM-130B more popular on GitHub? awesome-LLM-resources has more GitHub stars (8,845 vs 7,656). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-LLM-resources and GLM-130B open source? Yes - both are open-source projects on GitHub (awesome-LLM-resources: Apache-2.0, GLM-130B: Apache-2.0). ### Where can I find alternatives to awesome-LLM-resources or GLM-130B? GraphCanon lists graph-backed alternatives at [awesome-LLM-resources alternatives](/tools/wangrongsheng-awesome-llm-resources/alternatives) and [GLM-130B alternatives](/tools/zai-org-glm-130b/alternatives) ([awesome-LLM-resources markdown twin](/tools/wangrongsheng-awesome-llm-resources/alternatives.md), [GLM-130B markdown twin](/tools/zai-org-glm-130b/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/wangrongsheng-awesome-llm-resources-vs-zai-org-glm-130b.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-LLM-resources or GLM-130B? awesome-LLM-resources: Very active. GLM-130B: 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 awesome-LLM-resources and GLM-130B? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-LLM-resources trust report](/tools/wangrongsheng-awesome-llm-resources/trust); [GLM-130B trust report](/tools/zai-org-glm-130b/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=wangrongsheng-awesome-llm-resources`](/api/graphcanon/graph?tool=wangrongsheng-awesome-llm-resources) - 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/_