--- title: "scaling-book vs Large-Language-Model-Notebooks-Course" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/jax-ml-scaling-book-vs-peremartra-large-language-model-notebooks-course" tools: ["jax-ml-scaling-book", "peremartra-large-language-model-notebooks-course"] --- # scaling-book vs Large-Language-Model-Notebooks-Course *GraphCanon updated Aug 25, 2026* ## Verdict Pick scaling-book if scaling-book; 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. [scaling-book](https://jax-ml.github.io/scaling-book/) reports 1.4k GitHub stars, 191 forks, and 8 open issues, last pushed Aug 20, 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 [scaling-book's repository](https://github.com/jax-ml/scaling-book) and [Large-Language-Model-Notebooks-Course's repository](https://github.com/peremartra/Large-Language-Model-Notebooks-Course). | | [scaling-book](/tools/jax-ml-scaling-book.md) | [Large-Language-Model-Notebooks-Course](/tools/peremartra-large-language-model-notebooks-course.md) | | --- | --- | --- | | Tagline | Guide on scaling LLMs on TPUs | Practical course about Large Language Models | | Stars | 1,368 | 1,821 | | Forks | 191 | 447 | | Open issues | 8 | 0 | | Language | HTML | Jupyter Notebook | | Adopt for | scaling-book | A developing, comprehensive hands-on course covering a broad array of LLM tools and applications from OpenAI and Hugging Face. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Inference & Serving, LLM Frameworks | Evaluation & Observability, Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [scaling-book](/tools/jax-ml-scaling-book.md) | [Large-Language-Model-Notebooks-Course](/tools/peremartra-large-language-model-notebooks-course.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 4d | 79d | | Open issues (now) | 8 | 0 | | Stars delta | +77 (30d) | +3 (30d) | | Open issues delta | +1 (30d) | 0 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/jax-ml-scaling-book/trust.md) | [trust report](/tools/peremartra-large-language-model-notebooks-course/trust.md) | ## Decision facts: scaling-book - **Adopt for:** scaling-book ## 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 scaling-book if… - scaling-book is primarily HTML; Large-Language-Model-Notebooks-Course is Jupyter Notebook. - Tags unique to scaling-book: jax, llm-inference, llms, roofline. - You are working specifically with machine learning models that leverage Tensor Processing Units (TPUs) for performance and are looking to understand optimization techniques. ### Choose Large-Language-Model-Notebooks-Course if… - Large-Language-Model-Notebooks-Course is primarily Jupyter Notebook; scaling-book is HTML. - Tags unique to Large-Language-Model-Notebooks-Course: chatbots, fine-tuning-llm, huggingface, langchain. - Also covers Evaluation & Observability, Model Training. - You're seeking an evolving curriculum with projects that apply Large Language Model techniques from various libraries. ## When NOT to use scaling-book - Do not use if your project focuses exclusively on GPU scaling or other hardware not aligned with Tensor Processing Units (TPUs). - If you are looking for a general approach to any framework's scalability without emphasis on TPUs. - This resource is unsuitable if you need information about model training phases, as it emphasizes inference and serving phases. ## 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 scaling-book and Large-Language-Model-Notebooks-Course? scaling-book: Guide on scaling LLMs on TPUs. 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 scaling-book over Large-Language-Model-Notebooks-Course? Choose scaling-book over Large-Language-Model-Notebooks-Course when scaling-book is primarily HTML; Large-Language-Model-Notebooks-Course is Jupyter Notebook; Tags unique to scaling-book: jax, llm-inference, llms, roofline; You are working specifically with machine learning models that leverage Tensor Processing Units (TPUs) for performance and are looking to understand optimization techniques. ### When should I choose Large-Language-Model-Notebooks-Course over scaling-book? Choose Large-Language-Model-Notebooks-Course over scaling-book when Large-Language-Model-Notebooks-Course is primarily Jupyter Notebook; scaling-book is HTML; Tags unique to Large-Language-Model-Notebooks-Course: chatbots, fine-tuning-llm, huggingface, langchain; Also covers Evaluation & Observability, Model Training; You're seeking an evolving curriculum with projects that apply Large Language Model techniques from various libraries. ### When should I avoid scaling-book? Do not use if your project focuses exclusively on GPU scaling or other hardware not aligned with Tensor Processing Units (TPUs). If you are looking for a general approach to any framework's scalability without emphasis on TPUs. This resource is unsuitable if you need information about model training phases, as it emphasizes inference and serving phases. ### 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 scaling-book or Large-Language-Model-Notebooks-Course more popular on GitHub? Large-Language-Model-Notebooks-Course has more GitHub stars (1,821 vs 1,368). Stars measure visibility, not whether either tool fits your constraints. ### Are scaling-book and Large-Language-Model-Notebooks-Course open source? Yes - both are open-source projects on GitHub (scaling-book: MIT, Large-Language-Model-Notebooks-Course: MIT). ### Where can I find alternatives to scaling-book or Large-Language-Model-Notebooks-Course? GraphCanon lists graph-backed alternatives at [scaling-book alternatives](/tools/jax-ml-scaling-book/alternatives) and [Large-Language-Model-Notebooks-Course alternatives](/tools/peremartra-large-language-model-notebooks-course/alternatives) ([scaling-book markdown twin](/tools/jax-ml-scaling-book/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/jax-ml-scaling-book-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, scaling-book or Large-Language-Model-Notebooks-Course? scaling-book: 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 scaling-book and Large-Language-Model-Notebooks-Course? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [scaling-book trust report](/tools/jax-ml-scaling-book/trust); [Large-Language-Model-Notebooks-Course trust report](/tools/peremartra-large-language-model-notebooks-course/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=jax-ml-scaling-book`](/api/graphcanon/graph?tool=jax-ml-scaling-book) - 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/_