--- title: "moby vs ggrun" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/moby-moby-vs-raketenkater-ggrun" tools: ["moby-moby", "raketenkater-ggrun"] --- # moby vs ggrun *GraphCanon updated Jul 15, 2026* ## Verdict Pick moby when license: moby is Apache-2.0, ggrun is MIT; pick ggrun when license: ggrun is MIT, moby is Apache-2.0. [moby](https://mobyproject.org/) reports 72k GitHub stars, 19k forks, and 3.8k open issues, last pushed Jul 10, 2026. [ggrun](https://github.com/raketenkater/ggrun) has 254 stars, 14 forks, and 3 open issues, last pushed Jul 14, 2026. Figures are from public GitHub metadata via [moby's repository](https://github.com/moby/moby) and [ggrun's repository](https://github.com/raketenkater/ggrun). | | [moby](/tools/moby-moby.md) | [ggrun](/tools/raketenkater-ggrun.md) | | --- | --- | --- | | Tagline | The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems | Auto-tuned launcher for GGUF models on llama.cpp / ik_llama.cpp, OpenAI-compatible server with multi-GPU tensor-split, MoE expert placement, measured flag tuning (AI Tune), hardware-matched HuggingFac | | Stars | 71,899 | 254 | | Forks | 19,126 | 14 | | Open issues | 3,821 | 3 | | Language | Go | Go | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Developer Tools, Inference & Serving, LLM Frameworks | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [moby](/tools/moby-moby.md) | [ggrun](/tools/raketenkater-ggrun.md) | | --- | --- | --- | | Days since push | 1d | 0d | | Open issues (now) | 3.8k | 3 | | Owner type | Organization | User | | Full report | [trust report](/tools/moby-moby/trust.md) | [trust report](/tools/raketenkater-ggrun/trust.md) | ## Choose when ### Choose moby if… - License: moby is Apache-2.0, ggrun is MIT. - Tags unique to moby: containers, docker, go. - Also covers Developer Tools. - moby ships Docker support for self-hosted deployment. ### Choose ggrun if… - License: ggrun is MIT, moby is Apache-2.0. - Tags unique to ggrun: cuda, gguf, inference-server, llama-cpp. - More recently updated (last pushed Jul 14, 2026). ## 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. ## When NOT to use ggrun - 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 moby and ggrun? moby: The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems. ggrun: Auto-tuned launcher for GGUF models on llama.cpp / ik_llama.cpp, OpenAI-compatible server with multi-GPU tensor-split, MoE expert placement, measured flag tuning (AI Tune), hardware-matched HuggingFac. See the comparison table for live GitHub stats and shared categories. ### When should I choose moby over ggrun? Choose moby over ggrun when License: moby is Apache-2.0, ggrun is MIT; Tags unique to moby: containers, docker, go; Also covers Developer Tools; moby ships Docker support for self-hosted deployment. ### When should I choose ggrun over moby? Choose ggrun over moby when License: ggrun is MIT, moby is Apache-2.0; Tags unique to ggrun: cuda, gguf, inference-server, llama-cpp; More recently updated (last pushed Jul 14, 2026). ### 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. ### When should I avoid ggrun? 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 moby or ggrun more popular on GitHub? moby has more GitHub stars (71,899 vs 254). Stars measure visibility, not whether either tool fits your constraints. ### Are moby and ggrun open source? Yes - both are open-source projects on GitHub (moby: Apache-2.0, ggrun: MIT). ### Where can I find alternatives to moby or ggrun? GraphCanon lists graph-backed alternatives at [moby alternatives](/tools/moby-moby/alternatives) and [ggrun alternatives](/tools/raketenkater-ggrun/alternatives) ([moby markdown twin](/tools/moby-moby/alternatives.md), [ggrun markdown twin](/tools/raketenkater-ggrun/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/moby-moby-vs-raketenkater-ggrun.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, moby or ggrun? moby: Very active. ggrun: 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 moby and ggrun? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [moby trust report](/tools/moby-moby/trust); [ggrun trust report](/tools/raketenkater-ggrun/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=moby-moby`](/api/graphcanon/graph?tool=moby-moby) - 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/_