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This Support & Tips article explains how to tell whether a home server is ready for local AI workloads. It covers memory and VRAM pressure, model storage paths, Docker resource contention, GPU runtime detection, thermal and...

This guide explains how to verify whether a local LLM is using the correct model files and storage path. It covers runtime model lists, Docker host-to-container mounts, model metadata, GGUF and quantization checks, logs, active model...

This guide explains how to confirm whether hardware transcoding is actually working in Plex, Jellyfin, Emby, or Docker-based media servers. It covers forced transcode testing, dashboard signals, host GPU / iGPU activity, FFmpeg log paths, partial...

This guide explains how to safely deploy a local LLM on a shared home NAS or home server. It covers model storage paths, Docker volume mapping, memory and CPU limits, parallel requests, model choice, app isolation,...

This guide explains what to check before adding a GPU to a home NAS. It covers workload fit, PCIe slots, physical clearance, PSU headroom, cooling, driver support, Docker access, workload testing, and safer alternatives like iGPU...

This guide explains the local AI limits of a home NAS by workload type, hardware resources, and real-world impact. It covers OCR, media analysis, RAG, small LLMs, GPU / NPU acceleration, RAM / VRAM limits, warning...

This guide explains whether a home NAS can run local AI without a dedicated GPU. It covers CPU inference, RAM headroom, quantized models, Docker setups, AI search, offloading patterns, and how to test performance without disrupting...

This guide compares VPN, port forwarding, tunnels, and reverse proxies for home NAS remote access. It explains why VPN or mesh VPN is usually safer for private NAS access, when public exposure may be acceptable, and...