--- title: "LLM.swift vs moby" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/eastriverlee-llm-swift-vs-moby-moby" tools: ["eastriverlee-llm-swift", "moby-moby"] --- # LLM.swift vs moby *GraphCanon updated Jul 11, 2026* ## Verdict Pick LLM.swift when lLM.swift is primarily C++; moby is Go; pick moby when moby is primarily Go; LLM.swift is C++. [LLM.swift](https://github.com/eastriverlee/LLM.swift) reports 863 GitHub stars, 121 forks, and 16 open issues, last pushed Jul 4, 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 [LLM.swift's repository](https://github.com/eastriverlee/LLM.swift) and [moby's repository](https://github.com/moby/moby). | | [LLM.swift](/tools/eastriverlee-llm-swift.md) | [moby](/tools/moby-moby.md) | | --- | --- | --- | | Tagline | LLM.swift is a simple and readable library that allows you to interact with large language models locally with ease for macOS, iOS, watchOS, tvOS, and visionOS. | The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems | | Stars | 863 | 71,899 | | Forks | 121 | 19,126 | | Open issues | 16 | 3,821 | | Language | C++ | Go | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Computer Vision, Inference & Serving, LLM Frameworks | Developer Tools, Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LLM.swift](/tools/eastriverlee-llm-swift.md) | [moby](/tools/moby-moby.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 7d | 1d | | Open issues (now) | 16 | 3.8k | | Owner type | User | Organization | | Security scan | No lockfile | No criticals | | Full report | [trust report](/tools/eastriverlee-llm-swift/trust.md) | [trust report](/tools/moby-moby/trust.md) | ## Choose when ### Choose LLM.swift if… - LLM.swift is primarily C++; moby is Go. - License: LLM.swift is MIT, moby is Apache-2.0. - Tags unique to LLM.swift: gguf, ios, llm, llm-inference. - Also covers Computer Vision. ### Choose moby if… - moby is primarily Go; LLM.swift is C++. - License: moby is Apache-2.0, LLM.swift 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 LLM.swift - 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 LLM.swift and moby? LLM.swift: LLM.swift is a simple and readable library that allows you to interact with large language models locally with ease for macOS, iOS, watchOS, tvOS, and visionOS.. 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 LLM.swift over moby? Choose LLM.swift over moby when LLM.swift is primarily C++; moby is Go; License: LLM.swift is MIT, moby is Apache-2.0; Tags unique to LLM.swift: gguf, ios, llm, llm-inference; Also covers Computer Vision. ### When should I choose moby over LLM.swift? Choose moby over LLM.swift when moby is primarily Go; LLM.swift is C++; License: moby is Apache-2.0, LLM.swift 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 LLM.swift? 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 LLM.swift or moby more popular on GitHub? moby has more GitHub stars (71,899 vs 863). Stars measure visibility, not whether either tool fits your constraints. ### Are LLM.swift and moby open source? Yes - both are open-source projects on GitHub (LLM.swift: MIT, moby: Apache-2.0). ### Where can I find alternatives to LLM.swift or moby? GraphCanon lists graph-backed alternatives at [LLM.swift alternatives](/tools/eastriverlee-llm-swift/alternatives) and [moby alternatives](/tools/moby-moby/alternatives) ([LLM.swift markdown twin](/tools/eastriverlee-llm-swift/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/eastriverlee-llm-swift-vs-moby-moby.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LLM.swift or moby? LLM.swift: 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 LLM.swift and moby? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LLM.swift trust report](/tools/eastriverlee-llm-swift/trust); [moby trust report](/tools/moby-moby/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=eastriverlee-llm-swift`](/api/graphcanon/graph?tool=eastriverlee-llm-swift) - 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/_