--- title: "jan vs wllama" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/janhq-jan-vs-ngxson-wllama" tools: ["janhq-jan", "ngxson-wllama"] --- # jan vs wllama *GraphCanon updated Jul 11, 2026* ## Verdict Pick jan when license: jan is Other, wllama is MIT; pick wllama when license: wllama is MIT, jan is Other. [jan](https://jan.ai/) reports 43k GitHub stars, 2.9k forks, and 387 open issues, last pushed Jul 10, 2026. [wllama](https://huggingface.co/spaces/ngxson/wllama) has 1.1k stars, 106 forks, and 50 open issues, last pushed Jun 17, 2026. Figures are from public GitHub metadata via [jan's repository](https://github.com/janhq/jan) and [wllama's repository](https://github.com/ngxson/wllama). | | [jan](/tools/janhq-jan.md) | [wllama](/tools/ngxson-wllama.md) | | --- | --- | --- | | Tagline | open source alternative to ChatGPT that runs offline locally | WebAssembly binding for llama.cpp - Enabling on-browser LLM inference | | Stars | 43,499 | 1,138 | | Forks | 2,896 | 106 | | Open issues | 387 | 50 | | Language | TypeScript | TypeScript | | Adopt for | Jan is a TypeScript-based, self-hosted chatbot application that acts as an offline alternative to services like ChatGPT. | - | | Persona | - | - | | Runtime | - | - | | License | Other | MIT | | Categories | LLM Frameworks, Inference & Serving | LLM Frameworks, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [jan](/tools/janhq-jan.md) | [wllama](/tools/ngxson-wllama.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 1d | 23d | | Open issues (now) | 387 | 50 | | Owner type | Organization | User | | Security scan | No lockfile | 9 low (9 low) | | Full report | [trust report](/tools/janhq-jan/trust.md) | [trust report](/tools/ngxson-wllama/trust.md) | ## Decision facts: jan - **Adopt for:** Jan is a TypeScript-based, self-hosted chatbot application that acts as an offline alternative to services like ChatGPT. ## Choose when ### Choose jan if… - License: jan is Other, wllama is MIT. - Tags unique to jan: tauri, self-hosted, chatgpt, gpt. - - If you require an offline-capable AI assistant for environments without internet access. ### Choose wllama if… - License: wllama is MIT, jan is Other. - Tags unique to wllama: webassembly, llama, typescript, wasm. - Leaner open-issue backlog (50). ## When NOT to use jan - - If you require real-time updates to the AI model, since Jan uses static local models which may not get frequent updates. - - When a vast knowledge base or continuous learning capabilities are essential, as Jan's offline nature constrains its ability to stay current with new information. ## When NOT to use wllama - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## Common questions ### What is the difference between jan and wllama? jan: open source alternative to ChatGPT that runs offline locally. 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 jan over wllama? Choose jan over wllama when License: jan is Other, wllama is MIT; Tags unique to jan: tauri, self-hosted, chatgpt, gpt; - If you require an offline-capable AI assistant for environments without internet access. ### When should I choose wllama over jan? Choose wllama over jan when License: wllama is MIT, jan is Other; Tags unique to wllama: webassembly, llama, typescript, wasm; Leaner open-issue backlog (50). ### When should I avoid jan? - If you require real-time updates to the AI model, since Jan uses static local models which may not get frequent updates. - When a vast knowledge base or continuous learning capabilities are essential, as Jan's offline nature constrains its ability to stay current with new information. ### When should I avoid wllama? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### Is jan or wllama more popular on GitHub? jan has more GitHub stars (43,499 vs 1,138). Stars measure visibility, not whether either tool fits your constraints. ### Are jan and wllama open source? Yes - both are open-source projects on GitHub (jan: Other, wllama: MIT). ### Where can I find alternatives to jan or wllama? GraphCanon lists graph-backed alternatives at [jan alternatives](/tools/janhq-jan/alternatives) and [wllama alternatives](/tools/ngxson-wllama/alternatives) ([jan markdown twin](/tools/janhq-jan/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/janhq-jan-vs-ngxson-wllama.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, jan or wllama? jan: Very active. wllama: 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 jan and wllama? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [jan trust report](/tools/janhq-jan/trust); [wllama trust report](/tools/ngxson-wllama/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=janhq-jan`](/api/graphcanon/graph?tool=janhq-jan) - 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/_