janhq/jan
Jan
Jan is a desktop application that functions as a local artificial intelligence model runtime and an open-standard API server. It enables the execution of large language models directly on local hardware, ensuring that data remains private and accessible offline while providing a unified interface for managing model weights and inference runtimes.
The platform distinguishes itself by offering a modular inference backend that allows users to swap execution engines based on hardware compatibility and performance needs. It acts as a cross-platform orchestrator, providing the ability to switch between local model files and remote cloud-based AI providers through a single interface. By exposing these capabilities via an open-standard server layer, the application supports the integration of local AI into external software and development tools.
Beyond its core runtime capabilities, the software provides an environment for configuring agentic workflows and autonomous task automation. It includes tools for managing server behaviors, such as network access, authentication, and remote tool execution, while maintaining state persistence through a local file-based database. The application is distributed as a cross-platform container to ensure consistent access to local files and system resources across different operating systems.
Features
- Local Model Runtimes - Executes large language models directly on local hardware by managing model weights and inference runtimes.
- Desktop AI Runtimes - Executes large language models directly on local hardware to ensure data privacy and offline performance.
- OpenAI-Compatible Servers - Exposes model capabilities through standard HTTP endpoints for integration with external applications.
- Hybrid AI Orchestrators - Executes large language models directly on hardware or connects to cloud services.
- Local API Servers - Launches a local server that provides standard-compliant endpoints to interact with hosted models.
- AI Clients - Listed in the “AI Clients” section of the Awesome Mac awesome list.
- AI & Machine Learning - Offline-first alternative to ChatGPT for desktop.
- Desktop Applications - Desktop application for local AI model execution.
- Inference and Serving - Offline-first alternative to ChatGPT.
- Inference Engines - Offline-first alternative to commercial chat services.
- Language Model Development - Local, offline-capable alternative for running LLMs.
- Local AI Assistants - Offline AI assistant with local CPU and GPU support.
- Local Model Deployment - Interface for running LLMs locally or connecting to remote APIs.
- Privacy-Focused AI Tools - Runs large language models directly on hardware to ensure data stays private and secure.
- API Server Layers - Exposes local model capabilities through standard HTTP endpoints for compatibility with existing tools.
- Agentic Workflow Environments - Provides tools for configuring advanced server behaviors and remote execution to support autonomous task automation.
- AI API Gateways - Shares local model capabilities through a standard-compliant API to enable agentic features.
- Inference Backends - Swaps between different underlying model execution engines to balance performance and hardware compatibility.
- Cross-Platform Model Orchestrators - Provides a unified interface for managing and switching between local model files and remote cloud-based AI providers.
- Model Orchestration Platforms - Configures and manages a mix of open-source and cloud-based models for specialized assistants.
- Model Provider Proxies - Routes requests to external cloud-based AI services through a unified interface.
- Desktop Application Wrappers - Wraps the application in a desktop container to provide a unified interface across different operating systems.
