CRUX

The CRUX project is a lightweight, x86-64 optimized Linux distribution designed for experienced users. It emphasizes simplicity, minimalism, and customization through a ports system inspired by BSD's ports collection. CRUX aims to provide a clean, straightforward environment for users who want to build and control their system from the ground up.

Key Features

  • Lightweight, minimalistic design
  • BSD-style ports system for package management
  • Focused on simplicity and flexibility
  • Compatible with modern x86_64 hardware

Use Cases

  • For advanced Linux users who prefer hands-on system management
  • Building custom Linux environments
  • Learning and experimentation with Linux internals

CRUX-ARM

CRUX-ARM is a port of the CRUX distribution targeted at ARM architecture devices, including both 32-bit and 64-bit ARM systems. It brings the minimalism and flexibility of CRUX to the growing ARM ecosystem, supporting devices such as the Raspberry Pi series, Orange Pi, Pine64, and more.

Key Features

  • Support for ARMv7 (32-bit) and ARMv8 (64-bit) architectures
  • Automated CI/CD pipelines for timely releases
  • Community-driven development and support
  • Suitable for embedded systems, servers, and IoT devices

Use Cases

  • ARM-based embedded Linux development
  • Home servers on ARM hardware
  • IoT prototyping and deployment
  • Lightweight ARM Linux environments

CRUX-RiscV

CRUX-RiscV is the arm of the CRUX project dedicated to the RISC-V architecture, an open standard instruction set architecture growing rapidly in popularity. CRUX-RiscV aims to provide a minimalist, flexible Linux experience tailored for RISC-V hardware such as the Orange Pi RV2.

Key Features

  • Native support for RISC-V hardware
  • Development fueled by community and hardware donations
  • Automated build and CI/CD integration
  • Suitable for edge computing, embedded systems, and development

Use Cases

  • Developing and deploying RISC-V Linux systems
  • Educational platform for RISC-V architecture
  • Testing and improving RISC-V open-source tools and kernels

FluxTuner

FluxTuner is a modern internet radio player for the terminal and desktop. It combines a fast, keyboard-oriented TUI with an experimental GTK4 desktop GUI, offering a lightweight and practical way to browse, organize, and play internet radio stations.

Built with Python, FluxTuner focuses on speed, usability, and modularity, while keeping the experience simple enough for daily use on both desktop and low-resource systems.

Key Features

  • Fast terminal user interface focused on keyboard-driven workflows
  • Experimental GTK4 desktop GUI
  • Internet radio station search by name, genre, and country
  • Favorites with custom names and tags
  • Persistent playlists and dynamic tag-based playlists
  • Modular playback backends using mpv or ffplay
  • Live stream metadata display when available
  • Theming support with live preview
  • Estimated data usage tracking

Use Cases

  • Listening to internet radio from the terminal
  • Lightweight desktop radio playback
  • Managing favorite stations and playlists
  • Using radio playback over SSH or on low-resource systems
  • Experimenting with Python TUI, GTK4, and modular playback backends

ai.vjml.es

ai.vjml.es is a personal, self-hosted AI image generation gallery powered by solar energy. The project explores how local hardware, renewable energy, automation, and generative AI can be combined to create a practical and independent image generation platform.

It is used to generate, collect, compare, and refine AI-created images, with a focus on wallpapers, concept art, portraits, and themed visual collections. Beyond the visual results, the project is also an experiment in running AI workloads on privately managed infrastructure instead of relying entirely on external cloud services.

Key Features

  • Self-hosted AI image generation environment
  • Solar-powered infrastructure
  • Gallery for generated images and visual experiments
  • Local AI workflows running on privately managed hardware
  • Support for different formats, themes, and visual styles
  • Prompt-driven creative automation
  • Focus on reproducibility, efficiency, and infrastructure independence

Use Cases

  • Generating wallpapers and visual assets
  • Testing local AI image generation models
  • Building themed image collections
  • Experimenting with prompts, styles, and automation
  • Exploring sustainable self-hosted AI infrastructure
  • Running creative AI workloads with renewable energy