Open Source AI Project


Jan is an open-source tool that allows users to run mainstream open-source large language models, such as Mistral, Llama, and Mixtral, 100% offline without writing a s...


Jan: Revolutionizing Accessibility to Large Language Models

Purpose: At its core, Jan emerges as a groundbreaking tool designed to democratize access to some of the most powerful open-source large language models (LLMs) available today, such as Mistral, Llama, and Mixtral. By enabling 100% offline operation, Jan seeks to cater to a diverse range of users who prefer or require local processing for reasons such as data privacy, internet connectivity limitations, or the desire for more control over their computational resources.


  • Code-Free Interaction: Jan stands out by eliminating the complexity often associated with running sophisticated LLMs. Users are not required to write a single line of code to deploy and interact with these models, making advanced AI technologies accessible to a broader audience without the need for programming skills.

  • Cross-Platform Compatibility: With support for major operating systems including Windows, Mac, and Linux, Jan ensures a wide user base can benefit from its capabilities. This inclusivity fosters a more diverse community of users and developers, contributing to the tool’s continuous improvement and adaptation.

  • User-Friendly Interface: The emphasis on a highly aesthetic and user-friendly UI is a testament to Jan’s commitment to usability. By prioritizing a seamless user experience, Jan lowers the entry barrier for individuals to explore and utilize large language models, irrespective of their technical expertise.

  • Hardware Flexibility: Jan’s support for various hardware architectures, including Nvidia GPU, Apple M series, Apple Intel, Linux Debian, and Windows x64, highlights its versatility. This flexibility ensures that users with different hardware setups can still leverage Jan’s capabilities, provided they meet the recommended specifications.


  • Enhanced Privacy and Security: By operating entirely offline, Jan offers an invaluable advantage in terms of privacy and security. Users can process sensitive data without the risk of exposing it over the internet, making Jan an ideal solution for handling confidential or proprietary information.

  • Optimized Performance: The recommendation for higher-end hardware specifications, including at least 12GB of VRAM and 16GB of RAM, although a threshold for entry, ensures that Jan can deliver optimal performance. Users with the necessary hardware can experience smooth and efficient interactions with large language models, maximizing the tool’s effectiveness.

  • Specialized Model Access: The requirement for a special method (‘magic’) to download models may initially seem like a hurdle. However, this approach ensures that users gain access to the latest and most compatible versions of LLMs, potentially offering a curated and optimized selection of models for offline use.

  • Empowerment Through Accessibility: By bringing AI directly to users’ desktops, Jan empowers individuals and organizations to explore and innovate with AI technologies on their own terms. This empowerment accelerates learning, development, and potentially new applications of LLMs that are tailored to specific needs or interests.

In essence, Jan represents a significant leap forward in making advanced AI technologies more accessible, user-friendly, and secure. Its combination of ease of use, hardware inclusivity, and commitment to privacy positions Jan as a valuable asset for anyone looking to explore the potential of large language models without the constraints of online operation.

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