--- title: "distributed-llama vs rkllama" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/b4rtaz-distributed-llama-vs-notpunchnox-rkllama" tools: ["b4rtaz-distributed-llama", "notpunchnox-rkllama"] --- # distributed-llama vs rkllama *GraphCanon updated Aug 25, 2026* ## Verdict Pick distributed-llama if distributed-llama is a C++ framework that leverages multiple home devices for faster large language model inference, under the MIT license; pick rkllama if ollama alternative for Rockchip NPU: optimized AI and deep learning inference on Rockchip devices. [distributed-llama](https://github.com/b4rtaz/distributed-llama) reports 3.0k GitHub stars, 246 forks, and 48 open issues, last pushed Jul 5, 2026. [rkllama](https://github.com/NotPunchnox/rkllama) has 590 stars, 99 forks, and 65 open issues, last pushed Jul 7, 2026. Figures are from public GitHub metadata via [distributed-llama's repository](https://github.com/b4rtaz/distributed-llama) and [rkllama's repository](https://github.com/NotPunchnox/rkllama). | | [distributed-llama](/tools/b4rtaz-distributed-llama.md) | [rkllama](/tools/notpunchnox-rkllama.md) | | --- | --- | --- | | Tagline | Distributed LLM inference using home devices cluster | Ollama alternative for Rockchip NPU with optimized AI and Deep learning model inference | | Stars | 3,044 | 590 | | Forks | 246 | 99 | | Open issues | 48 | 65 | | Language | C++ | Python | | Adopt for | distributed-llama is a C++ framework that leverages multiple home devices for faster large language model inference, under the MIT license. | Ollama alternative for Rockchip NPU: optimized AI and deep learning inference on Rockchip devices | | Persona | - | - | | Runtime | - | - | | License | MIT | GPL-3.0 | | Categories | Inference & Serving | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [distributed-llama](/tools/b4rtaz-distributed-llama.md) | [rkllama](/tools/notpunchnox-rkllama.md) | | --- | --- | --- | | Days since push | 50d | 48d | | Open issues (now) | 48 | 65 | | Stars delta | +32 (30d) | +13 (30d) | | Open issues delta | 0 (30d) | +6 (30d) | | Full report | [trust report](/tools/b4rtaz-distributed-llama/trust.md) | [trust report](/tools/notpunchnox-rkllama/trust.md) | ## Decision facts: distributed-llama - **Adopt for:** distributed-llama is a C++ framework that leverages multiple home devices for faster large language model inference, under the MIT license. ## Decision facts: rkllama - **Adopt for:** Ollama alternative for Rockchip NPU: optimized AI and deep learning inference on Rockchip devices ## Choose when ### Choose distributed-llama if… - distributed-llama is primarily C++; rkllama is Python. - License: distributed-llama is MIT, rkllama is GPL-3.0. - Tags unique to distributed-llama: distributed-computing, neural-network. - When you have multiple interconnected home devices and want to maximize their combined computing power for LLM inference tasks. ### Choose rkllama if… - rkllama is primarily Python; distributed-llama is C++. - License: rkllama is GPL-3.0, distributed-llama is MIT. - Tags unique to rkllama: ai, client-server, npu-llm, orange-pi. - rkllama ships Docker support for self-hosted deployment. - You need to run models specifically optimized for Rockchip Neural Processing Unit (NPU) ## When NOT to use distributed-llama - For scenarios with fewer than two available devices, as the framework's capability to distribute and boost performance would be limited. - In professional environments that require strict data privacy controls, due to potential network vulnerabilities among home devices. ## 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 ## Common questions ### What is the difference between distributed-llama and rkllama? distributed-llama: Distributed LLM inference using home devices cluster. rkllama: Ollama alternative for Rockchip NPU with optimized AI and Deep learning model inference. See the comparison table for live GitHub stats and shared categories. ### When should I choose distributed-llama over rkllama? Choose distributed-llama over rkllama when distributed-llama is primarily C++; rkllama is Python; License: distributed-llama is MIT, rkllama is GPL-3.0; Tags unique to distributed-llama: distributed-computing, neural-network; When you have multiple interconnected home devices and want to maximize their combined computing power for LLM inference tasks. ### When should I choose rkllama over distributed-llama? Choose rkllama over distributed-llama when rkllama is primarily Python; distributed-llama is C++; License: rkllama is GPL-3.0, distributed-llama is MIT; Tags unique to rkllama: ai, client-server, npu-llm, orange-pi; rkllama ships Docker support for self-hosted deployment; You need to run models specifically optimized for Rockchip Neural Processing Unit (NPU). ### When should I avoid distributed-llama? For scenarios with fewer than two available devices, as the framework's capability to distribute and boost performance would be limited. In professional environments that require strict data privacy controls, due to potential network vulnerabilities among home devices. ### 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 ### Is distributed-llama or rkllama more popular on GitHub? distributed-llama has more GitHub stars (3,044 vs 590). Stars measure visibility, not whether either tool fits your constraints. ### Are distributed-llama and rkllama open source? Yes - both are open-source projects on GitHub (distributed-llama: MIT, rkllama: GPL-3.0). ### Where can I find alternatives to distributed-llama or rkllama? GraphCanon lists graph-backed alternatives at [distributed-llama alternatives](/tools/b4rtaz-distributed-llama/alternatives) and [rkllama alternatives](/tools/notpunchnox-rkllama/alternatives) ([distributed-llama markdown twin](/tools/b4rtaz-distributed-llama/alternatives.md), [rkllama markdown twin](/tools/notpunchnox-rkllama/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/b4rtaz-distributed-llama-vs-notpunchnox-rkllama.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, distributed-llama or rkllama? distributed-llama: Steady. rkllama: Steady. 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 distributed-llama and rkllama? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [distributed-llama trust report](/tools/b4rtaz-distributed-llama/trust); [rkllama trust report](/tools/notpunchnox-rkllama/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=b4rtaz-distributed-llama`](/api/graphcanon/graph?tool=b4rtaz-distributed-llama) - 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/_