--- title: "jan vs TurboLLM" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/janhq-jan-vs-mohitsoni48-turbollm" tools: ["janhq-jan", "mohitsoni48-turbollm"] --- # jan vs TurboLLM *GraphCanon updated Jul 15, 2026* ## Verdict Pick jan when tags unique to jan: chatgpt, gpt, llamacpp, llm; pick TurboLLM when tags unique to TurboLLM: ai, anthropic-api, claude code, gguf. [jan](https://jan.ai/) reports 43k GitHub stars, 2.9k forks, and 387 open issues, last pushed Jul 10, 2026. [TurboLLM](https://turbollm.dev) has 171 stars, 27 forks, and 2 open issues, last pushed Jul 15, 2026. Figures are from public GitHub metadata via [jan's repository](https://github.com/janhq/jan) and [TurboLLM's repository](https://github.com/mohitsoni48/TurboLLM). | | [jan](/tools/janhq-jan.md) | [TurboLLM](/tools/mohitsoni48-turbollm.md) | | --- | --- | --- | | Tagline | open source alternative to ChatGPT that runs offline locally | Run any local LLM engine, auto-tuned to your GPU, polished web UI + OpenAI/Anthropic-compatible API. Point Claude Code at your own machine in one command. No Electron, no Python, offline-first. | | Stars | 43,499 | 171 | | Forks | 2,896 | 27 | | Open issues | 387 | 2 | | 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 | - | | Categories | Inference & Serving, LLM Frameworks | Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [jan](/tools/janhq-jan.md) | [TurboLLM](/tools/mohitsoni48-turbollm.md) | | --- | --- | --- | | Days since push | 1d | 0d | | Open issues (now) | 387 | 2 | | Owner type | Organization | User | | Full report | [trust report](/tools/janhq-jan/trust.md) | [trust report](/tools/mohitsoni48-turbollm/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… - Tags unique to jan: chatgpt, gpt, llamacpp, llm. - - If you require an offline-capable AI assistant for environments without internet access. - More GitHub stars (43k vs 171) - visibility, not fit. ### Choose TurboLLM if… - Tags unique to TurboLLM: ai, anthropic-api, claude code, gguf. - More recently updated (last pushed Jul 15, 2026). ## 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 TurboLLM - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between jan and TurboLLM? jan: open source alternative to ChatGPT that runs offline locally. TurboLLM: Run any local LLM engine, auto-tuned to your GPU, polished web UI + OpenAI/Anthropic-compatible API. Point Claude Code at your own machine in one command. No Electron, no Python, offline-first.. See the comparison table for live GitHub stats and shared categories. ### When should I choose jan over TurboLLM? Choose jan over TurboLLM when Tags unique to jan: chatgpt, gpt, llamacpp, llm; - If you require an offline-capable AI assistant for environments without internet access; More GitHub stars (43k vs 171) - visibility, not fit. ### When should I choose TurboLLM over jan? Choose TurboLLM over jan when Tags unique to TurboLLM: ai, anthropic-api, claude code, gguf; More recently updated (last pushed Jul 15, 2026). ### 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 TurboLLM? Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is jan or TurboLLM more popular on GitHub? jan has more GitHub stars (43,499 vs 171). Stars measure visibility, not whether either tool fits your constraints. ### Are jan and TurboLLM open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to jan or TurboLLM? GraphCanon lists graph-backed alternatives at [jan alternatives](/tools/janhq-jan/alternatives) and [TurboLLM alternatives](/tools/mohitsoni48-turbollm/alternatives) ([jan markdown twin](/tools/janhq-jan/alternatives.md), [TurboLLM markdown twin](/tools/mohitsoni48-turbollm/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-mohitsoni48-turbollm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, jan or TurboLLM? jan: Very active. TurboLLM: 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 jan and TurboLLM? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [jan trust report](/tools/janhq-jan/trust); [TurboLLM trust report](/tools/mohitsoni48-turbollm/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/_