…for my media center Using a GPU to handle specific workloads is a must-have, depending on what you wish to achieve. For running a large language model (LLM), you absolutely need…
…between multiple local LLMs, but honestly, the only one right now that's capable enough for coding is Qwen3-Coder-Next, and until that changes, I don't need another running. That…
…an Nvidia RTX graphics card. Paperless-ngx doesn't demand too many resources or GPU power, but I combined it with a local LLM and WSL’s GPU pass-through, which helps…
…Sign in to your XDA account As much as I adore my local LLMs, they can’t hold a candle to the reasoning capabilities of their cloud counterparts, and for good reason…
…It ran smoothly on my setup through GPU offloading, even though it’s officially designed for 16GB of VRAM. For most things, it was fine. I would primarily prompt it for quick…
…It actually fits into my setup Integrations are simple Using a local LLM on its own is all good and well if it’s just for the purposes of extracting information. But…
…First is connecting different apps and systems, second is building LLM apps and RAG workflows, and third is running models locally for privacy. n8n fits into the first layer. It’s built…
…LLMs have a reputation for needing serious hardware, and I assumed the experience wouldn’t feel as smooth as the cloud-based tools I was used to. My writing workflow depends heavily…
…Related 7 things I wish I knew when I started self-hosting LLMs I've been self-hosting LLMs for quite a while now, and these are all of the things I…
…Related Your old GPU can still run big LLMs – you just need the right tweaks There's a lot you can do with these models Integrating local LLMs with VS Code increased…