--- title: "WizardLM vs awesome-LLM-resources" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/nlpxucan-wizardlm-vs-wangrongsheng-awesome-llm-resources" tools: ["nlpxucan-wizardlm", "wangrongsheng-awesome-llm-resources"] --- # WizardLM vs awesome-LLM-resources *GraphCanon updated Aug 17, 2026* ## Verdict Pick WizardLM if wizardLM powers language models like WizardCoder and WizardMath to excel in complex instruction handling; 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. [WizardLM](https://github.com/nlpxucan/WizardLM) reports 9.5k GitHub stars, 749 forks, and 169 open issues, last pushed Jun 7, 2025. [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 [WizardLM's repository](https://github.com/nlpxucan/WizardLM) and [awesome-LLM-resources's repository](https://github.com/WangRongsheng/awesome-LLM-resources). | | [WizardLM](/tools/nlpxucan-wizardlm.md) | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) | | --- | --- | --- | | Tagline | Empowering Large Pre-Trained Language Models to Follow Complex Instructions | Summary of the world's best LLM resources. | | Stars | 9,484 | 8,845 | | Forks | 749 | 950 | | Open issues | 169 | 23 | | Language | Python | - | | Adopt for | WizardLM powers language models like WizardCoder and WizardMath to excel in complex instruction handling. | 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 | (unknown) | Apache-2.0 | | Categories | LLM Frameworks, Model Training | AI Agents, Developer Tools, Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [WizardLM](/tools/nlpxucan-wizardlm.md) | [awesome-LLM-resources](/tools/wangrongsheng-awesome-llm-resources.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 424d | 2d | | Open issues (now) | 169 | 23 | | Stars delta | Unknown | +142 (30d) | | Open issues delta | Unknown | -13 (30d) | | Full report | [trust report](/tools/nlpxucan-wizardlm/trust.md) | [trust report](/tools/wangrongsheng-awesome-llm-resources/trust.md) | ## Decision facts: WizardLM - **Adopt for:** WizardLM powers language models like WizardCoder and WizardMath to excel in complex instruction handling. - **License detail:** (unknown) ## 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 WizardLM if… - Tags unique to WizardLM: instruction-following, wizardcoder, wizardmath. - When advanced coding tasks need precise solutions, surpassing GPT-3.5-Turbo and Gemini Pro - More GitHub stars (9.5k vs 8.8k) - visibility, not fit. ### Choose awesome-LLM-resources if… - Tags unique to awesome-LLM-resources: awesome-list, book, course, llama. - 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 NOT to use WizardLM - If real-time updates are needed beyond Nov 2023, as performance is based on past benchmarks - When looking for broad language capabilities of GPT-4, which outperformance in some benchmarks ## 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 WizardLM and awesome-LLM-resources? WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex Instructions. 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 WizardLM over awesome-LLM-resources? Choose WizardLM over awesome-LLM-resources when Tags unique to WizardLM: instruction-following, wizardcoder, wizardmath; When advanced coding tasks need precise solutions, surpassing GPT-3.5-Turbo and Gemini Pro; More GitHub stars (9.5k vs 8.8k) - visibility, not fit. ### When should I choose awesome-LLM-resources over WizardLM? Choose awesome-LLM-resources over WizardLM when Tags unique to awesome-LLM-resources: awesome-list, book, course, llama; 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 avoid WizardLM? If real-time updates are needed beyond Nov 2023, as performance is based on past benchmarks When looking for broad language capabilities of GPT-4, which outperformance in some benchmarks ### 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 WizardLM or awesome-LLM-resources more popular on GitHub? WizardLM has more GitHub stars (9,484 vs 8,845). Stars measure visibility, not whether either tool fits your constraints. ### Are WizardLM and awesome-LLM-resources open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to WizardLM or awesome-LLM-resources? GraphCanon lists graph-backed alternatives at [WizardLM alternatives](/tools/nlpxucan-wizardlm/alternatives) and [awesome-LLM-resources alternatives](/tools/wangrongsheng-awesome-llm-resources/alternatives) ([WizardLM markdown twin](/tools/nlpxucan-wizardlm/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/nlpxucan-wizardlm-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, WizardLM or awesome-LLM-resources? WizardLM: 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 WizardLM and awesome-LLM-resources? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [WizardLM trust report](/tools/nlpxucan-wizardlm/trust); [awesome-LLM-resources trust report](/tools/wangrongsheng-awesome-llm-resources/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=nlpxucan-wizardlm`](/api/graphcanon/graph?tool=nlpxucan-wizardlm) - 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/_