--- title: "wllama vs BrowserAI" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ngxson-wllama-vs-sauravpanda-browserai" tools: ["ngxson-wllama", "sauravpanda-browserai"] --- # wllama vs BrowserAI *GraphCanon updated Aug 25, 2026* ## Verdict Pick wllama if webAssembly bindings for browser-based inference of llama.cpp; pick BrowserAI if browserAI runs various local LLMs directly in your browser using TypeScript. [wllama](https://huggingface.co/spaces/ngxson/wllama) reports 1.2k GitHub stars, 117 forks, and 53 open issues, last pushed Jun 17, 2026. [BrowserAI](https://browserai.dev) has 1.4k stars, 138 forks, and 24 open issues, last pushed Jul 21, 2026. Figures are from public GitHub metadata via [wllama's repository](https://github.com/ngxson/wllama) and [BrowserAI's repository](https://github.com/sauravpanda/BrowserAI). | | [wllama](/tools/ngxson-wllama.md) | [BrowserAI](/tools/sauravpanda-browserai.md) | | --- | --- | --- | | Tagline | WebAssembly binding for llama.cpp - Enabling on-browser LLM inference | Run local LLMs like llama, deepseek-distill, kokoro and more inside your browser | | Stars | 1,159 | 1,449 | | Forks | 117 | 138 | | Open issues | 53 | 24 | | Language | TypeScript | TypeScript | | Adopt for | WebAssembly bindings for browser-based inference of llama.cpp. | BrowserAI runs various local LLMs directly in your browser using TypeScript. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Inference & Serving | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [wllama](/tools/ngxson-wllama.md) | [BrowserAI](/tools/sauravpanda-browserai.md) | | --- | --- | --- | | Days since push | 51d | 34d | | Open issues (now) | 53 | 24 | | Stars delta | Unknown | +3 (30d) | | Open issues delta | Unknown | 0 (30d) | | Full report | [trust report](/tools/ngxson-wllama/trust.md) | [trust report](/tools/sauravpanda-browserai/trust.md) | ## Decision facts: wllama - **Adopt for:** WebAssembly bindings for browser-based inference of llama.cpp. ## Decision facts: BrowserAI - **Adopt for:** BrowserAI runs various local LLMs directly in your browser using TypeScript. ## Choose when ### Choose wllama if… - Tags unique to wllama: llama, llamacpp, llm, wasm. - Need browser-based LLM inference directly through WebAssembly. ### Choose BrowserAI if… - Tags unique to BrowserAI: agents, ai, llm-inference, local. - Also covers LLM Frameworks. - You need to run local models like llama, deepseek-distill, kokoro inside the browser environment. ## 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. ## When NOT to use BrowserAI - You require a server-based solution instead of in-browser execution for LLMs. - The project involves extensive training tasks that are unsuitable for browser environments. ## Common questions ### What is the difference between wllama and BrowserAI? wllama: WebAssembly binding for llama.cpp - Enabling on-browser LLM inference. BrowserAI: Run local LLMs like llama, deepseek-distill, kokoro and more inside your browser. See the comparison table for live GitHub stats and shared categories. ### When should I choose wllama over BrowserAI? Choose wllama over BrowserAI when Tags unique to wllama: llama, llamacpp, llm, wasm; Need browser-based LLM inference directly through WebAssembly. ### When should I choose BrowserAI over wllama? Choose BrowserAI over wllama when Tags unique to BrowserAI: agents, ai, llm-inference, local; Also covers LLM Frameworks; You need to run local models like llama, deepseek-distill, kokoro inside the browser environment. ### 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. ### When should I avoid BrowserAI? You require a server-based solution instead of in-browser execution for LLMs. The project involves extensive training tasks that are unsuitable for browser environments. ### Is wllama or BrowserAI more popular on GitHub? BrowserAI has more GitHub stars (1,449 vs 1,159). Stars measure visibility, not whether either tool fits your constraints. ### Are wllama and BrowserAI open source? Yes - both are open-source projects on GitHub (wllama: MIT, BrowserAI: MIT). ### Where can I find alternatives to wllama or BrowserAI? GraphCanon lists graph-backed alternatives at [wllama alternatives](/tools/ngxson-wllama/alternatives) and [BrowserAI alternatives](/tools/sauravpanda-browserai/alternatives) ([wllama markdown twin](/tools/ngxson-wllama/alternatives.md), [BrowserAI markdown twin](/tools/sauravpanda-browserai/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/ngxson-wllama-vs-sauravpanda-browserai.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, wllama or BrowserAI? wllama: Steady. BrowserAI: 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 wllama and BrowserAI? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [wllama trust report](/tools/ngxson-wllama/trust); [BrowserAI trust report](/tools/sauravpanda-browserai/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ngxson-wllama`](/api/graphcanon/graph?tool=ngxson-wllama) - 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/_