ComfyUI Setup Guide for Beginners: Unleash Local AI Image Generation Welcome back to Self-Hosted Tech! If you’ve been hanging around the homelab and local AI communities lately, you’ve probably heard the name “Stable Diffusion” thrown around a lot. And if you’ve looked into running Stable Diffusion locally, you’ve undoubtedly seen screenshots of ComfyUI—a dizzying array of boxes and lines that looks like a hacker’s conspiracy board. ...

Corsair Novablade Pro & 8Bitdo Pro 2 Controllers Get Native Support in Linux 7.3-Rc7 Hey there, homelabbers! Welcome back to Self-Hosted Tech. When we talk about self-hosting, homelabs, and local AI, our minds usually jump straight to Docker containers, Proxmox clusters, Kubernetes manifests, and Ollama models running on repurposed GPUs. But today, we’re taking a slight detour into a category that is just as important to the modern homelabber: hardware and gaming. ...

Gmktec Evo-X3 Mini-PC Review: Looking at a 128GB AMD Local AI Box Welcome back to Self-Hosted Tech. If you’ve been hanging around the homelab and self-hosting community for a while, you already know that RAM is king. But when you start dipping your toes into the deep end of the pool with local AI, RAM becomes the emperor, the grand vizier, and the entire royal court all at once. We’ve seen a massive influx of mini-PCs hitting the market lately, but almost all of them cap out at 32GB or maybe 64GB of RAM. That’s fine for running a few Docker containers or a small Proxmox cluster, but it’s a massive bottleneck for running large language models (LLMs) locally. Enter the Gmktec Evo-X3. ...

Quantization Explained: Making LLMs Fit Your GPU If you’ve spent any time in the homelab or local AI space recently, you’ve probably run into the same frustrating wall we all do. You read about an amazing new open-source Large Language Model (LLM) like Llama 3 or Mistral. You excitedly fire up your terminal, download the model, hit “Run,” and then… boom. CUDA out of memory. Tried to allocate 2.00 GiB... ...

What is MoE (Mixture of Experts) in LLMs? If you’ve been hanging out in the local AI and self-hosting communities for the last few months, you’ve probably heard the term “MoE” thrown around. Maybe you saw someone on Reddit raving about Mixtral, or you saw a new model release on Hugging Face touting “Mixture of Experts” architecture. ...

AMD Ryzen AI Developer Platform OS Updated with ROCm 10.0 and Linux 7.2: What It Means for Your Homelab Hey everyone, welcome back to Self-Hosted Tech. If you’ve been following the local AI and self-hosting scene, you know that the hardware landscape has been shifting rapidly. We’re moving away from the idea that you need a massive, power-hungry, $2,000 GPU just to run a decent local Large Language Model (LLM) or process computer vision tasks. ...

Asus AI Tech 2026 Seoul: Bringing Edge AI to the Homelab Hey everyone, welcome back to Self-Hosted Tech. If you’ve been following the channel for a while, you know we are massive fans of running things locally. Whether it’s your media server, your smart home dashboard, or your password manager, keeping your data inside your own four walls is what the homelab lifestyle is all about. ...

Vulkan API Improvements Coming For The AMD Polaris Gpus With Mesa Radv If you’re anything like me, your homelab closet is a graveyard of older hardware. Among the dusty motherboards, tangled Ethernet cables, and retired power supplies, there’s a good chance you have an older AMD graphics card sitting in an anti-static bag. Specifically, I’m talking about the Polaris generation—the legendary RX 400 and RX 500 series cards. ...

How I Used Guilt As A Motivator For Good If you’re reading this on the Self-Hosted Tech blog, I can safely assume a few things about you. You probably have a stack of hard drives somewhere in your house. You likely have a dusty Raspberry Pi or two in a drawer. And, if you’re anything like me, you have a creeping, persistent sense of guilt about the hardware you’ve bought, provisioned, and then left to sit idle. ...

Introducing Web Search API Via AI Gateway If you’ve been hanging around the homelab community for any amount of time, you know that our setups evolve. We start with a simple Raspberry Pi running Pi-hole, move on to a NAS for our media, and eventually, we find ourselves racking servers in our closets to run our own AI models. Welcome to the modern homelab. As local AI has exploded, thanks to projects like Ollama, text-generation-webui, and vLLM, we’ve run into a very familiar problem: our local Large Language Models (LLMs) are trapped in time. They know everything up to their training cutoff date, but ask them who won the game last night or what the current weather is in your city, and they’ll confidently hallucinate an answer. ...