--- title: "Awesome-Multimodal-Large-Language-Models vs Large-Language-Model-Notebooks-Course" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/bradyfu-awesome-multimodal-large-language-models-vs-peremartra-large-language-model-notebooks-course" tools: ["bradyfu-awesome-multimodal-large-language-models", "peremartra-large-language-model-notebooks-course"] --- # Awesome-Multimodal-Large-Language-Models vs Large-Language-Model-Notebooks-Course *GraphCanon updated Aug 17, 2026* ## Verdict Pick Awesome-Multimodal-Large-Language-Models if awesome-Multimodal-Large-Language-Models is a curated collection of surveys and benchmarks focused on multimodal large language models (MLLMs), encompassing evaluation frameworks, interactive Omni MLLMs, and benchmarking; pick Large-Language-Model-Notebooks-Course if a developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face. [Awesome-Multimodal-Large-Language-Models](https://github.com/BradyFU/Awesome-Multimodal-Large-Language-Models) reports 18k GitHub stars, 1.1k forks, and 111 open issues, last pushed Aug 14, 2026. [Large-Language-Model-Notebooks-Course](https://medium.com/@peremartra/list/large-language-models-practical-course-66b4ce5943ce) has 1.8k stars, 447 forks, and 0 open issues, last pushed May 28, 2026. Figures are from public GitHub metadata via [Awesome-Multimodal-Large-Language-Models's repository](https://github.com/BradyFU/Awesome-Multimodal-Large-Language-Models) and [Large-Language-Model-Notebooks-Course's repository](https://github.com/peremartra/Large-Language-Model-Notebooks-Course). | | [Awesome-Multimodal-Large-Language-Models](/tools/bradyfu-awesome-multimodal-large-language-models.md) | [Large-Language-Model-Notebooks-Course](/tools/peremartra-large-language-model-notebooks-course.md) | | --- | --- | --- | | Tagline | Latest Advances on Multimodal Large Language Models | Practical course about Large Language Models | | Stars | 17,978 | 1,821 | | Forks | 1,133 | 447 | | Open issues | 111 | 0 | | Language | - | Jupyter Notebook | | Adopt for | Awesome-Multimodal-Large-Language-Models is a curated collection of surveys and benchmarks focused on multimodal large language models (MLLMs), encompassing evaluation frameworks, interactive Omni MLLMs, and benchmarking | A developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face. | | Persona | - | - | | Runtime | - | - | | License | - | MIT | | Categories | Evaluation & Observability, LLM Frameworks | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Awesome-Multimodal-Large-Language-Models](/tools/bradyfu-awesome-multimodal-large-language-models.md) | [Large-Language-Model-Notebooks-Course](/tools/peremartra-large-language-model-notebooks-course.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 2d | 79d | | Open issues (now) | 111 | 0 | | Stars delta | +29 (30d) | +3 (30d) | | Open issues delta | +4 (30d) | 0 (30d) | | Full report | [trust report](/tools/bradyfu-awesome-multimodal-large-language-models/trust.md) | [trust report](/tools/peremartra-large-language-model-notebooks-course/trust.md) | ## Decision facts: Awesome-Multimodal-Large-Language-Models - **Adopt for:** Awesome-Multimodal-Large-Language-Models is a curated collection of surveys and benchmarks focused on multimodal large language models (MLLMs), encompassing evaluation frameworks, interactive Omni MLLMs, and benchmarking ## Decision facts: Large-Language-Model-Notebooks-Course - **Adopt for:** A developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face. ## Choose when ### Choose Awesome-Multimodal-Large-Language-Models if… - Tags unique to Awesome-Multimodal-Large-Language-Models: chain-of-thought, in-context-learning, instruction-following, instruction-tuning. - - You need comprehensive resources for evaluating multimodal LLMs and want access to the latest research findings in this area. - More GitHub stars (18k vs 1.8k) - visibility, not fit. ### Choose Large-Language-Model-Notebooks-Course if… - Tags unique to Large-Language-Model-Notebooks-Course: chatbots, fine-tuning-llm, huggingface, langchain. - Also covers Inference & Serving, Model Training. - You're seeking an evolving curriculum with projects that apply Large Language Model techniques from various libraries. ## When NOT to use Awesome-Multimodal-Large-Language-Models - - If your primary focus is on single-modality language models, without a need to integrate visual or audio elements. - - If you prefer tools that provide hands-on implementation guidance rather than surveys and benchmarks for theoretical exploration. ## When NOT to use Large-Language-Model-Notebooks-Course - Seeking a complete, finalized course where all content is available for immediate use without future updates. - Looking exclusively for theory; the course emphasizes practical application over theoretical depth. ## Common questions ### What is the difference between Awesome-Multimodal-Large-Language-Models and Large-Language-Model-Notebooks-Course? Awesome-Multimodal-Large-Language-Models: Latest Advances on Multimodal Large Language Models. Large-Language-Model-Notebooks-Course: Practical course about Large Language Models. See the comparison table for live GitHub stats and shared categories. ### When should I choose Awesome-Multimodal-Large-Language-Models over Large-Language-Model-Notebooks-Course? Choose Awesome-Multimodal-Large-Language-Models over Large-Language-Model-Notebooks-Course when Tags unique to Awesome-Multimodal-Large-Language-Models: chain-of-thought, in-context-learning, instruction-following, instruction-tuning; - You need comprehensive resources for evaluating multimodal LLMs and want access to the latest research findings in this area; More GitHub stars (18k vs 1.8k) - visibility, not fit. ### When should I choose Large-Language-Model-Notebooks-Course over Awesome-Multimodal-Large-Language-Models? Choose Large-Language-Model-Notebooks-Course over Awesome-Multimodal-Large-Language-Models when Tags unique to Large-Language-Model-Notebooks-Course: chatbots, fine-tuning-llm, huggingface, langchain; Also covers Inference & Serving, Model Training; You're seeking an evolving curriculum with projects that apply Large Language Model techniques from various libraries. ### When should I avoid Awesome-Multimodal-Large-Language-Models? - If your primary focus is on single-modality language models, without a need to integrate visual or audio elements. - If you prefer tools that provide hands-on implementation guidance rather than surveys and benchmarks for theoretical exploration. ### When should I avoid Large-Language-Model-Notebooks-Course? Seeking a complete, finalized course where all content is available for immediate use without future updates. Looking exclusively for theory; the course emphasizes practical application over theoretical depth. ### Is Awesome-Multimodal-Large-Language-Models or Large-Language-Model-Notebooks-Course more popular on GitHub? Awesome-Multimodal-Large-Language-Models has more GitHub stars (17,978 vs 1,821). Stars measure visibility, not whether either tool fits your constraints. ### Are Awesome-Multimodal-Large-Language-Models and Large-Language-Model-Notebooks-Course open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to Awesome-Multimodal-Large-Language-Models or Large-Language-Model-Notebooks-Course? GraphCanon lists graph-backed alternatives at [Awesome-Multimodal-Large-Language-Models alternatives](/tools/bradyfu-awesome-multimodal-large-language-models/alternatives) and [Large-Language-Model-Notebooks-Course alternatives](/tools/peremartra-large-language-model-notebooks-course/alternatives) ([Awesome-Multimodal-Large-Language-Models markdown twin](/tools/bradyfu-awesome-multimodal-large-language-models/alternatives.md), [Large-Language-Model-Notebooks-Course markdown twin](/tools/peremartra-large-language-model-notebooks-course/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/bradyfu-awesome-multimodal-large-language-models-vs-peremartra-large-language-model-notebooks-course.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Awesome-Multimodal-Large-Language-Models or Large-Language-Model-Notebooks-Course? Awesome-Multimodal-Large-Language-Models: Very active. Large-Language-Model-Notebooks-Course: Steady. 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-Multimodal-Large-Language-Models and Large-Language-Model-Notebooks-Course? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [Awesome-Multimodal-Large-Language-Models trust report](/tools/bradyfu-awesome-multimodal-large-language-models/trust); [Large-Language-Model-Notebooks-Course trust report](/tools/peremartra-large-language-model-notebooks-course/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=bradyfu-awesome-multimodal-large-language-models`](/api/graphcanon/graph?tool=bradyfu-awesome-multimodal-large-language-models) - 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/_