--- title: "rkllama vs ggrun" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/notpunchnox-rkllama-vs-raketenkater-ggrun" tools: ["notpunchnox-rkllama", "raketenkater-ggrun"] --- # rkllama vs ggrun *GraphCanon updated Aug 25, 2026* ## Verdict Pick rkllama if ollama alternative for Rockchip NPU: optimized AI and deep learning inference on Rockchip devices; pick ggrun if ggrun, an auto-tuned launcher for GGUF models using llama.cpp, offers OpenAI-compatible server support with multi-GPU tensor-split and MoE expert placement capabilities. [rkllama](https://github.com/NotPunchnox/rkllama) reports 590 GitHub stars, 99 forks, and 65 open issues, last pushed Jul 7, 2026. [ggrun](https://github.com/raketenkater/ggrun) has 264 stars, 14 forks, and 1 open issues, last pushed Aug 11, 2026. Figures are from public GitHub metadata via [rkllama's repository](https://github.com/NotPunchnox/rkllama) and [ggrun's repository](https://github.com/raketenkater/ggrun). | | [rkllama](/tools/notpunchnox-rkllama.md) | [ggrun](/tools/raketenkater-ggrun.md) | | --- | --- | --- | | Tagline | Ollama alternative for Rockchip NPU with optimized AI and Deep learning model inference | Auto-tuned launcher for GGUF models on llama.cpp with OpenAI-compatible server | | Stars | 590 | 264 | | Forks | 99 | 14 | | Open issues | 65 | 1 | | Language | Python | Go | | Adopt for | Ollama alternative for Rockchip NPU: optimized AI and deep learning inference on Rockchip devices | ggrun, an auto-tuned launcher for GGUF models using llama.cpp, offers OpenAI-compatible server support with multi-GPU tensor-split and MoE expert placement capabilities. | | Persona | - | - | | Runtime | - | - | | License | GPL-3.0 | MIT License allows using ggrun freely in both open source and commercial projects, with conditions that the copyright notice and permission notice are preserved. | | Categories | Inference & Serving | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [rkllama](/tools/notpunchnox-rkllama.md) | [ggrun](/tools/raketenkater-ggrun.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 48d | 1d | | Open issues (now) | 65 | 1 | | Stars delta | +13 (30d) | Unknown | | Open issues delta | +6 (30d) | Unknown | | Full report | [trust report](/tools/notpunchnox-rkllama/trust.md) | [trust report](/tools/raketenkater-ggrun/trust.md) | ## Decision facts: rkllama - **Adopt for:** Ollama alternative for Rockchip NPU: optimized AI and deep learning inference on Rockchip devices ## Decision facts: ggrun - **Pricing:** freemium - Free to use under MIT license; no direct costs involved in usage. - **Adopt for:** ggrun, an auto-tuned launcher for GGUF models using llama.cpp, offers OpenAI-compatible server support with multi-GPU tensor-split and MoE expert placement capabilities. - **License detail:** MIT License allows using ggrun freely in both open source and commercial projects, with conditions that the copyright notice and permission notice are preserved. ## Choose when ### Choose rkllama if… - rkllama is primarily Python; ggrun is Go. - License: rkllama is GPL-3.0, ggrun is MIT. - Tags unique to rkllama: ai, client-server, llm-inference, npu-llm. - rkllama ships Docker support for self-hosted deployment. - You need to run models specifically optimized for Rockchip Neural Processing Unit (NPU) ### Choose ggrun if… - ggrun is primarily Go; rkllama is Python. - License: ggrun is MIT, rkllama is GPL-3.0. - Pricing: Free to use under MIT license; no direct costs involved in usage.. - Tags unique to ggrun: cuda, gguf, golang, inference-server. - When developing systems that require automatic hardware optimization and tuning for GGUF models on multiple GPUs ## When NOT to use rkllama - Your hardware does not include a Rockchip NPU - You are looking for an AI solution that works across multiple non-Rockchip platforms ## When NOT to use ggrun - For environments where single-GPU setups are preferred, as ggrun specializes in multi-GPU configurations and may offer limited advantage or additional complexity - When you do not require auto-tuning capabilities for hardware performance optimization since this feature is specific to ggrun ## Common questions ### What is the difference between rkllama and ggrun? rkllama: Ollama alternative for Rockchip NPU with optimized AI and Deep learning model inference. ggrun: Auto-tuned launcher for GGUF models on llama.cpp with OpenAI-compatible server. See the comparison table for live GitHub stats and shared categories. ### When should I choose rkllama over ggrun? Choose rkllama over ggrun when rkllama is primarily Python; ggrun is Go; License: rkllama is GPL-3.0, ggrun is MIT; Tags unique to rkllama: ai, client-server, llm-inference, npu-llm; rkllama ships Docker support for self-hosted deployment; You need to run models specifically optimized for Rockchip Neural Processing Unit (NPU). ### When should I choose ggrun over rkllama? Choose ggrun over rkllama when ggrun is primarily Go; rkllama is Python; License: ggrun is MIT, rkllama is GPL-3.0; Pricing: Free to use under MIT license; no direct costs involved in usage.; Tags unique to ggrun: cuda, gguf, golang, inference-server; When developing systems that require automatic hardware optimization and tuning for GGUF models on multiple GPUs. ### When should I avoid rkllama? Your hardware does not include a Rockchip NPU You are looking for an AI solution that works across multiple non-Rockchip platforms ### When should I avoid ggrun? For environments where single-GPU setups are preferred, as ggrun specializes in multi-GPU configurations and may offer limited advantage or additional complexity When you do not require auto-tuning capabilities for hardware performance optimization since this feature is specific to ggrun ### Is rkllama or ggrun more popular on GitHub? rkllama has more GitHub stars (590 vs 264). Stars measure visibility, not whether either tool fits your constraints. ### Are rkllama and ggrun open source? Yes - both are open-source projects on GitHub (rkllama: GPL-3.0, ggrun: MIT). ### Where can I find alternatives to rkllama or ggrun? GraphCanon lists graph-backed alternatives at [rkllama alternatives](/tools/notpunchnox-rkllama/alternatives) and [ggrun alternatives](/tools/raketenkater-ggrun/alternatives) ([rkllama markdown twin](/tools/notpunchnox-rkllama/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/notpunchnox-rkllama-vs-raketenkater-ggrun.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, rkllama or ggrun? rkllama: Steady. 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 rkllama and ggrun? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [rkllama trust report](/tools/notpunchnox-rkllama/trust); [ggrun trust report](/tools/raketenkater-ggrun/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=notpunchnox-rkllama`](/api/graphcanon/graph?tool=notpunchnox-rkllama) - 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/_