--- title: "rig vs shimmy" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/0xplaygrounds-rig-vs-michael-a-kuykendall-shimmy" tools: ["0xplaygrounds-rig", "michael-a-kuykendall-shimmy"] --- # rig vs shimmy *GraphCanon updated Sep 30, 2026* ## Verdict Pick rig if rig is a Rust library designed to create modular and scalable LLM applications with extensive support for agentic workflows, multi-turn streaming, full compatibility with GenAI conventions, and integration capabilities; pick shimmy if shimmy is a Rust-based inference engine that supports WebGPU for local machine learning model inference, compatible with the OpenAI API and GGUF models, offering a. [rig](https://rig.rs) reports 8.7k GitHub stars, 974 forks, and 102 open issues, last pushed Sep 19, 2026. [shimmy](https://github.com/Michael-A-Kuykendall/shimmy) has 5.9k stars, 576 forks, and 10 open issues, last pushed Aug 30, 2026. Figures are from public GitHub metadata via [rig's repository](https://github.com/0xPlaygrounds/rig) and [shimmy's repository](https://github.com/Michael-A-Kuykendall/shimmy). | | [rig](/tools/0xplaygrounds-rig.md) | [shimmy](/tools/michael-a-kuykendall-shimmy.md) | | --- | --- | --- | | Tagline | Build modular and scalable LLM Applications in Rust | Pure-Rust WebGPU inference engine, OpenAI-API compatible, GGUF native | | Stars | 8,679 | 5,890 | | Forks | 974 | 576 | | Open issues | 102 | 10 | | Language | Rust | Rust | | Adopt for | Rig is a Rust library designed to create modular and scalable LLM applications with extensive support for agentic workflows, multi-turn streaming, full compatibility with GenAI conventions, and integration capabilities. | Shimmy is a Rust-based inference engine that supports WebGPU for local machine learning model inference, compatible with the OpenAI API and GGUF models, offering a command-line interface. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents, LLM Frameworks | Developer Tools, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [rig](/tools/0xplaygrounds-rig.md) | [shimmy](/tools/michael-a-kuykendall-shimmy.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 18d | | Open issues (now) | 102 | 10 | | Stars delta | +351 (30d) | +193 (30d) | | Open issues delta | -11 (30d) | -1 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/0xplaygrounds-rig/trust.md) | [trust report](/tools/michael-a-kuykendall-shimmy/trust.md) | ## Decision facts: rig - **Hosting:** self hosted - Self-hosted as a Rust library. - **Pricing:** freemium - Free to use under MIT license with potential premium support options. - **Adopt for:** Rig is a Rust library designed to create modular and scalable LLM applications with extensive support for agentic workflows, multi-turn streaming, full compatibility with GenAI conventions, and integration capabilities. - **License detail:** MIT ## Decision facts: shimmy - **Requirements:** Shimmy requires a GPU for optimal performance.; The tool is designed to be used with GGUF models and is compatible with the OpenAI API. - **Adopt for:** Shimmy is a Rust-based inference engine that supports WebGPU for local machine learning model inference, compatible with the OpenAI API and GGUF models, offering a command-line interface. - **License detail:** Apache-2.0 ## Choose when ### Choose rig if… - License: rig is MIT, shimmy is Apache-2.0. - Self-hosted as a Rust library. - Pricing: Free to use under MIT license with potential premium support options.. - Tags unique to rig: agent, ai, artificial-intelligence, automation. - Also covers AI Agents, LLM Frameworks. - You should use Rig when you need to work with LLM applications in Rust and want full WASM (core library) compatibility. ### Choose shimmy if… - License: shimmy is Apache-2.0, rig is MIT. - Requirements: Shimmy requires a GPU for optimal performance.; The tool is designed to be used with GGUF models and is compatible with the OpenAI API.. - Tags unique to shimmy: api-server, command-line-tool, gguf, huggingface. - Also covers Developer Tools, Inference & Serving. - shimmy ships Docker support for self-hosted deployment. - When you need a Rust-based inference engine that supports WebGPU for running machine learning models locally. ## When NOT to use rig - Avoid using Rig if you are working on applications that do not require or support Rust as it is specifically built to facilitate LLM operations within a Rust environment. - Rig may not be suitable if your project cannot handle potential breaking changes, which are expected due to its rapidly evolving nature and upcoming feature updates. ## When NOT to use shimmy - If you require a solution that supports languages other than Rust or frameworks that are not WebGPU-based. - When you need a tool that integrates with Python or llama.cpp, as Shimmy explicitly avoids these dependencies. - If you are looking for a multi-component system; Shimmy is designed as a single binary for simplicity. - When you need a paid product with additional features or support, as Shimmy is committed to being free forever. ## Common questions ### What is the difference between rig and shimmy? rig: Build modular and scalable LLM Applications in Rust. shimmy: Pure-Rust WebGPU inference engine, OpenAI-API compatible, GGUF native. See the comparison table for live GitHub stats and shared categories. ### When should I choose rig over shimmy? Choose rig over shimmy when License: rig is MIT, shimmy is Apache-2.0; Self-hosted as a Rust library; Pricing: Free to use under MIT license with potential premium support options.; Tags unique to rig: agent, ai, artificial-intelligence, automation; Also covers AI Agents, LLM Frameworks; You should use Rig when you need to work with LLM applications in Rust and want full WASM (core library) compatibility. ### When should I choose shimmy over rig? Choose shimmy over rig when License: shimmy is Apache-2.0, rig is MIT; Requirements: Shimmy requires a GPU for optimal performance.; The tool is designed to be used with GGUF models and is compatible with the OpenAI API.; Tags unique to shimmy: api-server, command-line-tool, gguf, huggingface; Also covers Developer Tools, Inference & Serving; shimmy ships Docker support for self-hosted deployment; When you need a Rust-based inference engine that supports WebGPU for running machine learning models locally. ### When should I avoid rig? Avoid using Rig if you are working on applications that do not require or support Rust as it is specifically built to facilitate LLM operations within a Rust environment. Rig may not be suitable if your project cannot handle potential breaking changes, which are expected due to its rapidly evolving nature and upcoming feature updates. ### When should I avoid shimmy? If you require a solution that supports languages other than Rust or frameworks that are not WebGPU-based. When you need a tool that integrates with Python or llama.cpp, as Shimmy explicitly avoids these dependencies. If you are looking for a multi-component system; Shimmy is designed as a single binary for simplicity. When you need a paid product with additional features or support, as Shimmy is committed to being free forever. ### Is rig or shimmy more popular on GitHub? rig has more GitHub stars (8,679 vs 5,890). Stars measure visibility, not whether either tool fits your constraints. ### Are rig and shimmy open source? Yes - both are open-source projects on GitHub (rig: MIT, shimmy: Apache-2.0). ### Where can I find alternatives to rig or shimmy? GraphCanon lists graph-backed alternatives at [rig alternatives](/tools/0xplaygrounds-rig/alternatives) and [shimmy alternatives](/tools/michael-a-kuykendall-shimmy/alternatives) ([rig markdown twin](/tools/0xplaygrounds-rig/alternatives.md), [shimmy markdown twin](/tools/michael-a-kuykendall-shimmy/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/0xplaygrounds-rig-vs-michael-a-kuykendall-shimmy.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, rig or shimmy? rig: Very active. shimmy: 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 rig and shimmy? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [rig trust report](/tools/0xplaygrounds-rig/trust); [shimmy trust report](/tools/michael-a-kuykendall-shimmy/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=0xplaygrounds-rig`](/api/graphcanon/graph?tool=0xplaygrounds-rig) - 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/_