--- title: "scaling-book vs moby" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/jax-ml-scaling-book-vs-moby-moby" tools: ["jax-ml-scaling-book", "moby-moby"] --- # scaling-book vs moby *GraphCanon updated Jul 11, 2026* ## Verdict Pick scaling-book when scaling-book is primarily HTML; moby is Go; pick moby when moby is primarily Go; scaling-book is HTML. [scaling-book](https://jax-ml.github.io/scaling-book/) reports 1.3k GitHub stars, 179 forks, and 8 open issues, last pushed Jul 8, 2026. [moby](https://mobyproject.org/) has 72k stars, 19k forks, and 3.8k open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [scaling-book's repository](https://github.com/jax-ml/scaling-book) and [moby's repository](https://github.com/moby/moby). | | [scaling-book](/tools/jax-ml-scaling-book.md) | [moby](/tools/moby-moby.md) | | --- | --- | --- | | Tagline | Home for "How To Scale Your Model", a short blog-style textbook about scaling LLMs on TPUs | The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems | | Stars | 1,258 | 71,899 | | Forks | 179 | 19,126 | | Open issues | 8 | 3,821 | | Language | HTML | Go | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Inference & Serving, LLM Frameworks | Developer Tools, Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [scaling-book](/tools/jax-ml-scaling-book.md) | [moby](/tools/moby-moby.md) | | --- | --- | --- | | Days since push | 2d | 1d | | Open issues (now) | 8 | 3.8k | | Security scan | No lockfile | No criticals | | Full report | [trust report](/tools/jax-ml-scaling-book/trust.md) | [trust report](/tools/moby-moby/trust.md) | ## Choose when ### Choose scaling-book if… - scaling-book is primarily HTML; moby is Go. - License: scaling-book is MIT, moby is Apache-2.0. - Tags unique to scaling-book: html, jax, llm-inference, llms. ### Choose moby if… - moby is primarily Go; scaling-book is HTML. - License: moby is Apache-2.0, scaling-book is MIT. - Tags unique to moby: containers, docker, go, golang. - Also covers Developer Tools. - moby ships Docker support for self-hosted deployment. ## When NOT to use scaling-book - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use moby - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between scaling-book and moby? scaling-book: Home for "How To Scale Your Model", a short blog-style textbook about scaling LLMs on TPUs. moby: The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems. See the comparison table for live GitHub stats and shared categories. ### When should I choose scaling-book over moby? Choose scaling-book over moby when scaling-book is primarily HTML; moby is Go; License: scaling-book is MIT, moby is Apache-2.0; Tags unique to scaling-book: html, jax, llm-inference, llms. ### When should I choose moby over scaling-book? Choose moby over scaling-book when moby is primarily Go; scaling-book is HTML; License: moby is Apache-2.0, scaling-book is MIT; Tags unique to moby: containers, docker, go, golang; Also covers Developer Tools; moby ships Docker support for self-hosted deployment. ### When should I avoid scaling-book? Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid moby? Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is scaling-book or moby more popular on GitHub? moby has more GitHub stars (71,899 vs 1,258). Stars measure visibility, not whether either tool fits your constraints. ### Are scaling-book and moby open source? Yes - both are open-source projects on GitHub (scaling-book: MIT, moby: Apache-2.0). ### Where can I find alternatives to scaling-book or moby? GraphCanon lists graph-backed alternatives at [scaling-book alternatives](/tools/jax-ml-scaling-book/alternatives) and [moby alternatives](/tools/moby-moby/alternatives) ([scaling-book markdown twin](/tools/jax-ml-scaling-book/alternatives.md), [moby markdown twin](/tools/moby-moby/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-moby-moby.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, scaling-book or moby? scaling-book: Very active. moby: Very active. 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 moby? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [scaling-book trust report](/tools/jax-ml-scaling-book/trust); [moby trust report](/tools/moby-moby/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/_