--- title: "distributed-llama vs wllama" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/b4rtaz-distributed-llama-vs-ngxson-wllama" tools: ["b4rtaz-distributed-llama", "ngxson-wllama"] --- # distributed-llama vs wllama *GraphCanon updated Aug 24, 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 wllama if webAssembly bindings for browser-based inference of llama.cpp. [distributed-llama](https://github.com/b4rtaz/distributed-llama) reports 3.0k GitHub stars, 246 forks, and 48 open issues, last pushed Jul 5, 2026. [wllama](https://huggingface.co/spaces/ngxson/wllama) has 1.2k stars, 117 forks, and 53 open issues, last pushed Jun 17, 2026. Figures are from public GitHub metadata via [distributed-llama's repository](https://github.com/b4rtaz/distributed-llama) and [wllama's repository](https://github.com/ngxson/wllama). | | [distributed-llama](/tools/b4rtaz-distributed-llama.md) | [wllama](/tools/ngxson-wllama.md) | | --- | --- | --- | | Tagline | Distributed LLM inference using home devices cluster | WebAssembly binding for llama.cpp - Enabling on-browser LLM inference | | Stars | 3,044 | 1,159 | | Forks | 246 | 117 | | Open issues | 48 | 53 | | Language | C++ | TypeScript | | Adopt for | distributed-llama is a C++ framework that leverages multiple home devices for faster large language model inference, under the MIT license. | WebAssembly bindings for browser-based inference of llama.cpp. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Inference & Serving | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [distributed-llama](/tools/b4rtaz-distributed-llama.md) | [wllama](/tools/ngxson-wllama.md) | | --- | --- | --- | | Days since push | 50d | 51d | | Open issues (now) | 48 | 53 | | Stars delta | +32 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Full report | [trust report](/tools/b4rtaz-distributed-llama/trust.md) | [trust report](/tools/ngxson-wllama/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: wllama - **Adopt for:** WebAssembly bindings for browser-based inference of llama.cpp. ## Choose when ### Choose distributed-llama if… - distributed-llama is primarily C++; wllama is TypeScript. - Tags unique to distributed-llama: distributed-computing, llm-inference, neural-network. - When you have multiple interconnected home devices and want to maximize their combined computing power for LLM inference tasks. ### Choose wllama if… - wllama is primarily TypeScript; distributed-llama is C++. - Tags unique to wllama: llama, llamacpp, llm, wasm. - Need browser-based LLM inference directly through WebAssembly. ## 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 wllama - Require direct native execution speed benefits unavailable in a WebAssembly context. - Developing server-side applications without the need for client-side inference capabilities. ## Common questions ### What is the difference between distributed-llama and wllama? distributed-llama: Distributed LLM inference using home devices cluster. wllama: WebAssembly binding for llama.cpp - Enabling on-browser LLM inference. See the comparison table for live GitHub stats and shared categories. ### When should I choose distributed-llama over wllama? Choose distributed-llama over wllama when distributed-llama is primarily C++; wllama is TypeScript; Tags unique to distributed-llama: distributed-computing, llm-inference, 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 wllama over distributed-llama? Choose wllama over distributed-llama when wllama is primarily TypeScript; distributed-llama is C++; Tags unique to wllama: llama, llamacpp, llm, wasm; Need browser-based LLM inference directly through WebAssembly. ### 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 wllama? Require direct native execution speed benefits unavailable in a WebAssembly context. Developing server-side applications without the need for client-side inference capabilities. ### Is distributed-llama or wllama more popular on GitHub? distributed-llama has more GitHub stars (3,044 vs 1,159). Stars measure visibility, not whether either tool fits your constraints. ### Are distributed-llama and wllama open source? Yes - both are open-source projects on GitHub (distributed-llama: MIT, wllama: MIT). ### Where can I find alternatives to distributed-llama or wllama? GraphCanon lists graph-backed alternatives at [distributed-llama alternatives](/tools/b4rtaz-distributed-llama/alternatives) and [wllama alternatives](/tools/ngxson-wllama/alternatives) ([distributed-llama markdown twin](/tools/b4rtaz-distributed-llama/alternatives.md), [wllama markdown twin](/tools/ngxson-wllama/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-ngxson-wllama.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, distributed-llama or wllama? distributed-llama: Steady. wllama: 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 wllama? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [distributed-llama trust report](/tools/b4rtaz-distributed-llama/trust); [wllama trust report](/tools/ngxson-wllama/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/_