--- title: "awesome-prompts vs Awesome-AIGC-Tutorials" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ai-boost-awesome-prompts-vs-luban-agi-awesome-aigc-tutorials" tools: ["ai-boost-awesome-prompts", "luban-agi-awesome-aigc-tutorials"] --- # awesome-prompts vs Awesome-AIGC-Tutorials *GraphCanon updated Jul 28, 2026* ## Verdict Pick awesome-prompts if awesome-prompts is a collection of rated GPT prompts from the GPTs Store with a focus on engineering, attacks, protections, and academic papers; pick Awesome-AIGC-Tutorials if awesome-AIGC-Tutorials supplies specialized guidance on Large Language Models and AI-generated artistry. [awesome-prompts](https://awesomegpt.vip) reports 8.4k GitHub stars, 798 forks, and 35 open issues, last pushed Jul 11, 2026. [Awesome-AIGC-Tutorials](https://github.com/luban-agi/Awesome-AIGC-Tutorials) has 4.5k stars, 303 forks, and 10 open issues, last pushed Mar 31, 2024. Figures are from public GitHub metadata via [awesome-prompts's repository](https://github.com/ai-boost/awesome-prompts) and [Awesome-AIGC-Tutorials's repository](https://github.com/luban-agi/Awesome-AIGC-Tutorials). | | [awesome-prompts](/tools/ai-boost-awesome-prompts.md) | [Awesome-AIGC-Tutorials](/tools/luban-agi-awesome-aigc-tutorials.md) | | --- | --- | --- | | Tagline | Curated chatgpt prompts and advanced prompt engineering papers | Curated tutorials and resources for Large Language Models, AI Painting, and more | | Stars | 8,440 | 4,522 | | Forks | 798 | 303 | | Open issues | 35 | 10 | | Language | - | - | | Adopt for | awesome-prompts is a collection of rated GPT prompts from the GPTs Store with a focus on engineering, attacks, protections, and academic papers. | Awesome-AIGC-Tutorials supplies specialized guidance on Large Language Models and AI-generated artistry. | | Persona | - | - | | Runtime | - | - | | License | GPL-3.0 | MIT license allows for free use in both open-source and proprietary products, with attribution required to the authors. | | Categories | Developer Tools | Developer Tools, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-prompts](/tools/ai-boost-awesome-prompts.md) | [Awesome-AIGC-Tutorials](/tools/luban-agi-awesome-aigc-tutorials.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 848d | | Open issues (now) | 35 | 10 | | Owner type | User | Organization | | Full report | [trust report](/tools/ai-boost-awesome-prompts/trust.md) | [trust report](/tools/luban-agi-awesome-aigc-tutorials/trust.md) | ## Decision facts: awesome-prompts - **Adopt for:** awesome-prompts is a collection of rated GPT prompts from the GPTs Store with a focus on engineering, attacks, protections, and academic papers. ## Decision facts: Awesome-AIGC-Tutorials - **Requirements:** No specific technical prerequisites are listed. Basic understanding of AI concepts like LLMs and NLP is beneficial. - **Adopt for:** Awesome-AIGC-Tutorials supplies specialized guidance on Large Language Models and AI-generated artistry. - **License detail:** MIT license allows for free use in both open-source and proprietary products, with attribution required to the authors. ## Choose when ### Choose awesome-prompts if… - License: awesome-prompts is GPL-3.0, Awesome-AIGC-Tutorials is MIT. - Tags unique to awesome-prompts: awesome-list, prompt-attack, prompt-engineering, prompt-protect. - Need detailed prompt engineering resources ### Choose Awesome-AIGC-Tutorials if… - License: Awesome-AIGC-Tutorials is MIT, awesome-prompts is GPL-3.0. - Requirements: No specific technical prerequisites are listed. Basic understanding of AI concepts like LLMs and NLP is beneficial.. - Tags unique to Awesome-AIGC-Tutorials: ai, aigc, deep-learning, llm. - Also covers LLM Frameworks, Model Training. - If you aim to deepen your understanding of prompt engineering for models like MidJourney or Stable Diffusion, this repository offers focused tutorials and resources. ## When NOT to use awesome-prompts - Seeking a platform for generating new prompts rather than reviewing existing ones - In search of direct support tools or services, not just informational content - Requiring real-time collaboration on prompt creation and experimentation ## When NOT to use Awesome-AIGC-Tutorials - Avoid if you are looking for a one-stop-shop coding platform, as Awesome-AIGC-Tutorials provides theoretical knowledge and tutorials rather than practical code samples. - Not suitable if your focus is solely on the commercial deployment of large language models; this repository does not cover market-specific insights or competitive analysis. ## Common questions ### What is the difference between awesome-prompts and Awesome-AIGC-Tutorials? awesome-prompts: Curated chatgpt prompts and advanced prompt engineering papers. Awesome-AIGC-Tutorials: Curated tutorials and resources for Large Language Models, AI Painting, and more. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-prompts over Awesome-AIGC-Tutorials? Choose awesome-prompts over Awesome-AIGC-Tutorials when License: awesome-prompts is GPL-3.0, Awesome-AIGC-Tutorials is MIT; Tags unique to awesome-prompts: awesome-list, prompt-attack, prompt-engineering, prompt-protect; Need detailed prompt engineering resources. ### When should I choose Awesome-AIGC-Tutorials over awesome-prompts? Choose Awesome-AIGC-Tutorials over awesome-prompts when License: Awesome-AIGC-Tutorials is MIT, awesome-prompts is GPL-3.0; Requirements: No specific technical prerequisites are listed. Basic understanding of AI concepts like LLMs and NLP is beneficial.; Tags unique to Awesome-AIGC-Tutorials: ai, aigc, deep-learning, llm; Also covers LLM Frameworks, Model Training; If you aim to deepen your understanding of prompt engineering for models like MidJourney or Stable Diffusion, this repository offers focused tutorials and resources. ### When should I avoid awesome-prompts? Seeking a platform for generating new prompts rather than reviewing existing ones In search of direct support tools or services, not just informational content Requiring real-time collaboration on prompt creation and experimentation ### When should I avoid Awesome-AIGC-Tutorials? Avoid if you are looking for a one-stop-shop coding platform, as Awesome-AIGC-Tutorials provides theoretical knowledge and tutorials rather than practical code samples. Not suitable if your focus is solely on the commercial deployment of large language models; this repository does not cover market-specific insights or competitive analysis. ### Is awesome-prompts or Awesome-AIGC-Tutorials more popular on GitHub? awesome-prompts has more GitHub stars (8,440 vs 4,522). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-prompts and Awesome-AIGC-Tutorials open source? Yes - both are open-source projects on GitHub (awesome-prompts: GPL-3.0, Awesome-AIGC-Tutorials: MIT). ### Where can I find alternatives to awesome-prompts or Awesome-AIGC-Tutorials? GraphCanon lists graph-backed alternatives at [awesome-prompts alternatives](/tools/ai-boost-awesome-prompts/alternatives) and [Awesome-AIGC-Tutorials alternatives](/tools/luban-agi-awesome-aigc-tutorials/alternatives) ([awesome-prompts markdown twin](/tools/ai-boost-awesome-prompts/alternatives.md), [Awesome-AIGC-Tutorials markdown twin](/tools/luban-agi-awesome-aigc-tutorials/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/ai-boost-awesome-prompts-vs-luban-agi-awesome-aigc-tutorials.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, awesome-prompts or Awesome-AIGC-Tutorials? awesome-prompts: Very active. Awesome-AIGC-Tutorials: 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-prompts and Awesome-AIGC-Tutorials? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-prompts trust report](/tools/ai-boost-awesome-prompts/trust); [Awesome-AIGC-Tutorials trust report](/tools/luban-agi-awesome-aigc-tutorials/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ai-boost-awesome-prompts`](/api/graphcanon/graph?tool=ai-boost-awesome-prompts) - 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/_