--- title: "AI-Infra-from-Zero-to-Hero vs LLMSurvey" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/huaizhengzhang-ai-infra-from-zero-to-hero-vs-rucaibox-llmsurvey" tools: ["huaizhengzhang-ai-infra-from-zero-to-hero", "rucaibox-llmsurvey"] --- # AI-Infra-from-Zero-to-Hero vs LLMSurvey *GraphCanon updated Sep 20, 2026* ## Verdict Pick AI-Infra-from-Zero-to-Hero if a curated resource list for AI system design focusing on large language models and various system aspects; pick LLMSurvey if lLMSurvey is a repository that provides a comprehensive survey paper and resources on Large Language Models, including a beginner-friendly Chinese book and detailed content on long chain-of-thought reasoning. [AI-Infra-from-Zero-to-Hero](https://huaizheng.xyz/) reports 4.3k GitHub stars, 409 forks, and 14 open issues, last pushed Jul 25, 2025. [LLMSurvey](https://arxiv.org/abs/2303.18223) has 12k stars, 930 forks, and 30 open issues, last pushed Mar 11, 2025. Figures are from public GitHub metadata via [AI-Infra-from-Zero-to-Hero's repository](https://github.com/HuaizhengZhang/AI-Infra-from-Zero-to-Hero) and [LLMSurvey's repository](https://github.com/RUCAIBox/LLMSurvey). | | [AI-Infra-from-Zero-to-Hero](/tools/huaizhengzhang-ai-infra-from-zero-to-hero.md) | [LLMSurvey](/tools/rucaibox-llmsurvey.md) | | --- | --- | --- | | Tagline | Awesome System for Machine Learning and LLM Infra | A collection of papers and resources related to Large Language Models | | Stars | 4,285 | 12,216 | | Forks | 409 | 930 | | Open issues | 14 | 30 | | Language | - | Python | | Adopt for | A curated resource list for AI system design focusing on large language models and various system aspects. | LLMSurvey is a repository that provides a comprehensive survey paper and resources on Large Language Models, including a beginner-friendly Chinese book and detailed content on long chain-of-thought reasoning. | | Persona | - | - | | Runtime | - | - | | License | MIT | The license information for LLMSurvey is unknown. | | Categories | Developer Tools, Inference & Serving, LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [AI-Infra-from-Zero-to-Hero](/tools/huaizhengzhang-ai-infra-from-zero-to-hero.md) | [LLMSurvey](/tools/rucaibox-llmsurvey.md) | | --- | --- | --- | | Days since push | 388d | 555d | | Open issues (now) | 14 | 30 | | Stars delta | +87 (30d) | +11 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/huaizhengzhang-ai-infra-from-zero-to-hero/trust.md) | [trust report](/tools/rucaibox-llmsurvey/trust.md) | ## Decision facts: AI-Infra-from-Zero-to-Hero - **Adopt for:** A curated resource list for AI system design focusing on large language models and various system aspects. ## Decision facts: LLMSurvey - **Pricing:** freemium - The repository is free to access, but the Chinese book is available for purchase. - **Requirements:** Min 4 GB RAM; A basic understanding of deep learning is recommended for the Chinese book. - **Adopt for:** LLMSurvey is a repository that provides a comprehensive survey paper and resources on Large Language Models, including a beginner-friendly Chinese book and detailed content on long chain-of-thought reasoning. - **License detail:** The license information for LLMSurvey is unknown. ## Choose when ### Choose AI-Infra-from-Zero-to-Hero if… - Tags unique to AI-Infra-from-Zero-to-Hero: ai-infra, genai, llmsys, mlsys. - Also covers Developer Tools, Inference & Serving. - When you are aiming to understand the foundational research papers, industry practices, video tutorials specific to ML systems and LLM infrastructures without requiring implementation details. ### Choose LLMSurvey if… - Pricing: The repository is free to access, but the Chinese book is available for purchase.. - Requirements: Min 4 GB RAM; A basic understanding of deep learning is recommended for the Chinese book.. - Tags unique to LLMSurvey: chain-of-thought, chatgpt, in-context-learning, instruction-tuning. - Use LLMSurvey when you need a detailed survey paper and resources on Large Language Models, especially if you are interested in long chain-of-thought reasoning. ## When NOT to use AI-Infra-from-Zero-to-Hero - If you need step-by-step implementations for AI infrastructure setup as the repository focuses on resources rather than detailed technical instructions. - Avoid if seeking guidance specifically for real-time system deployment and tuning, since it does not cover operational tactics in depth. ## When NOT to use LLMSurvey - Avoid LLMSurvey if you are looking for a tool that provides hands-on training or implementation of LLMs, as it focuses more on theoretical resources and surveys. - Do not use LLMSurvey if you require real-time updates or interactive tools for LLM development, as it primarily offers static content and resources. ## Common questions ### What is the difference between AI-Infra-from-Zero-to-Hero and LLMSurvey? AI-Infra-from-Zero-to-Hero: Awesome System for Machine Learning and LLM Infra. LLMSurvey: A collection of papers and resources related to Large Language Models. See the comparison table for live GitHub stats and shared categories. ### When should I choose AI-Infra-from-Zero-to-Hero over LLMSurvey? Choose AI-Infra-from-Zero-to-Hero over LLMSurvey when Tags unique to AI-Infra-from-Zero-to-Hero: ai-infra, genai, llmsys, mlsys; Also covers Developer Tools, Inference & Serving; When you are aiming to understand the foundational research papers, industry practices, video tutorials specific to ML systems and LLM infrastructures without requiring implementation details. ### When should I choose LLMSurvey over AI-Infra-from-Zero-to-Hero? Choose LLMSurvey over AI-Infra-from-Zero-to-Hero when Pricing: The repository is free to access, but the Chinese book is available for purchase.; Requirements: Min 4 GB RAM; A basic understanding of deep learning is recommended for the Chinese book.; Tags unique to LLMSurvey: chain-of-thought, chatgpt, in-context-learning, instruction-tuning; Use LLMSurvey when you need a detailed survey paper and resources on Large Language Models, especially if you are interested in long chain-of-thought reasoning. ### When should I avoid AI-Infra-from-Zero-to-Hero? If you need step-by-step implementations for AI infrastructure setup as the repository focuses on resources rather than detailed technical instructions. Avoid if seeking guidance specifically for real-time system deployment and tuning, since it does not cover operational tactics in depth. ### When should I avoid LLMSurvey? Avoid LLMSurvey if you are looking for a tool that provides hands-on training or implementation of LLMs, as it focuses more on theoretical resources and surveys. Do not use LLMSurvey if you require real-time updates or interactive tools for LLM development, as it primarily offers static content and resources. ### Is AI-Infra-from-Zero-to-Hero or LLMSurvey more popular on GitHub? LLMSurvey has more GitHub stars (12,216 vs 4,285). Stars measure visibility, not whether either tool fits your constraints. ### Are AI-Infra-from-Zero-to-Hero and LLMSurvey open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to AI-Infra-from-Zero-to-Hero or LLMSurvey? GraphCanon lists graph-backed alternatives at [AI-Infra-from-Zero-to-Hero alternatives](/tools/huaizhengzhang-ai-infra-from-zero-to-hero/alternatives) and [LLMSurvey alternatives](/tools/rucaibox-llmsurvey/alternatives) ([AI-Infra-from-Zero-to-Hero markdown twin](/tools/huaizhengzhang-ai-infra-from-zero-to-hero/alternatives.md), [LLMSurvey markdown twin](/tools/rucaibox-llmsurvey/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/huaizhengzhang-ai-infra-from-zero-to-hero-vs-rucaibox-llmsurvey.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, AI-Infra-from-Zero-to-Hero or LLMSurvey? AI-Infra-from-Zero-to-Hero: Dormant. LLMSurvey: 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 AI-Infra-from-Zero-to-Hero and LLMSurvey? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [AI-Infra-from-Zero-to-Hero trust report](/tools/huaizhengzhang-ai-infra-from-zero-to-hero/trust); [LLMSurvey trust report](/tools/rucaibox-llmsurvey/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=huaizhengzhang-ai-infra-from-zero-to-hero`](/api/graphcanon/graph?tool=huaizhengzhang-ai-infra-from-zero-to-hero) - 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/_