--- title: "open-llms vs Awesome-AIGC-Tutorials" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/eugeneyan-open-llms-vs-luban-agi-awesome-aigc-tutorials" tools: ["eugeneyan-open-llms", "luban-agi-awesome-aigc-tutorials"] --- # open-llms vs Awesome-AIGC-Tutorials *GraphCanon updated Aug 17, 2026* ## Verdict Pick open-llms if critical Facts for 'open-llms' Tool Usage; pick Awesome-AIGC-Tutorials if awesome-AIGC-Tutorials supplies specialized guidance on Large Language Models and AI-generated artistry. [open-llms](https://github.com/eugeneyan/open-llms) reports 13k GitHub stars, 985 forks, and 11 open issues, last pushed Feb 13, 2025. [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 [open-llms's repository](https://github.com/eugeneyan/open-llms) and [Awesome-AIGC-Tutorials's repository](https://github.com/luban-agi/Awesome-AIGC-Tutorials). | | [open-llms](/tools/eugeneyan-open-llms.md) | [Awesome-AIGC-Tutorials](/tools/luban-agi-awesome-aigc-tutorials.md) | | --- | --- | --- | | Tagline | A list of open LLMs available for commercial use. | Curated tutorials and resources for Large Language Models, AI Painting, and more | | Stars | 12,849 | 4,522 | | Forks | 985 | 303 | | Open issues | 11 | 10 | | Language | - | - | | Adopt for | Critical Facts for 'open-llms' Tool Usage | Awesome-AIGC-Tutorials supplies specialized guidance on Large Language Models and AI-generated artistry. | | Persona | - | - | | Runtime | - | - | | License | The repository itself is licensed under the permissive Apache-2.0 license; however, it aggregates data about various LLMs that may have differing licensing conditions including but not limited to the | MIT license allows for free use in both open-source and proprietary products, with attribution required to the authors. | | Categories | LLM Frameworks | Developer Tools, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [open-llms](/tools/eugeneyan-open-llms.md) | [Awesome-AIGC-Tutorials](/tools/luban-agi-awesome-aigc-tutorials.md) | | --- | --- | --- | | Days since push | 549d | 848d | | Open issues (now) | 11 | 10 | | Stars delta | +18 (30d) | Unknown | | Open issues delta | -2 (30d) | Unknown | | Owner type | User | Organization | | Full report | [trust report](/tools/eugeneyan-open-llms/trust.md) | [trust report](/tools/luban-agi-awesome-aigc-tutorials/trust.md) | ## Decision facts: open-llms - **Pricing:** freemium - Free and open-source models for commercial use are listed here. Usage of the models themselves varies by license, with some possibly requiring contributions or acknowledgements. - **Adopt for:** Critical Facts for 'open-llms' Tool Usage - **License detail:** The repository itself is licensed under the permissive Apache-2.0 license; however, it aggregates data about various LLMs that may have differing licensing conditions including but not limited to the ## 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 open-llms if… - License: open-llms is Apache-2.0, Awesome-AIGC-Tutorials is MIT. - Pricing: Free and open-source models for commercial use are listed here. Usage of the models themselves varies by license, with some possibly requiring contributions or acknowledgements.. - Tags unique to open-llms: commercial, large language models, llms. - When you need a curated list of open-source large language models (LLMs) that are specifically licensed for commercial use. ### Choose Awesome-AIGC-Tutorials if… - License: Awesome-AIGC-Tutorials is MIT, open-llms is Apache-2.0. - 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, chatgpt, deep-learning. - Also covers Developer Tools, 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 open-llms - If you require proprietary or closed-source LLMs as this repository exclusively lists open-source models that are available for commercial use under permissive licenses such as Apache 2.0. - For projects needing a detailed technical implementation guide of each listed LLM, since 'open-llms' acts primarily as an index rather than providing in-depth tutorials on implementing and training L4 ## 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 open-llms and Awesome-AIGC-Tutorials? open-llms: A list of open LLMs available for commercial use.. 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 open-llms over Awesome-AIGC-Tutorials? Choose open-llms over Awesome-AIGC-Tutorials when License: open-llms is Apache-2.0, Awesome-AIGC-Tutorials is MIT; Pricing: Free and open-source models for commercial use are listed here. Usage of the models themselves varies by license, with some possibly requiring contributions or acknowledgements.; Tags unique to open-llms: commercial, large language models, llms; When you need a curated list of open-source large language models (LLMs) that are specifically licensed for commercial use. ### When should I choose Awesome-AIGC-Tutorials over open-llms? Choose Awesome-AIGC-Tutorials over open-llms when License: Awesome-AIGC-Tutorials is MIT, open-llms is Apache-2.0; 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, chatgpt, deep-learning; Also covers Developer Tools, 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 open-llms? If you require proprietary or closed-source LLMs as this repository exclusively lists open-source models that are available for commercial use under permissive licenses such as Apache 2.0. For projects needing a detailed technical implementation guide of each listed LLM, since 'open-llms' acts primarily as an index rather than providing in-depth tutorials on implementing and training L4 ### 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 open-llms or Awesome-AIGC-Tutorials more popular on GitHub? open-llms has more GitHub stars (12,849 vs 4,522). Stars measure visibility, not whether either tool fits your constraints. ### Are open-llms and Awesome-AIGC-Tutorials open source? Yes - both are open-source projects on GitHub (open-llms: Apache-2.0, Awesome-AIGC-Tutorials: MIT). ### Where can I find alternatives to open-llms or Awesome-AIGC-Tutorials? GraphCanon lists graph-backed alternatives at [open-llms alternatives](/tools/eugeneyan-open-llms/alternatives) and [Awesome-AIGC-Tutorials alternatives](/tools/luban-agi-awesome-aigc-tutorials/alternatives) ([open-llms markdown twin](/tools/eugeneyan-open-llms/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/eugeneyan-open-llms-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, open-llms or Awesome-AIGC-Tutorials? open-llms: Dormant. 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 open-llms and Awesome-AIGC-Tutorials? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [open-llms trust report](/tools/eugeneyan-open-llms/trust); [Awesome-AIGC-Tutorials trust report](/tools/luban-agi-awesome-aigc-tutorials/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=eugeneyan-open-llms`](/api/graphcanon/graph?tool=eugeneyan-open-llms) - 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/_