Fig 13Build your own personal AI boxGhost Core-style
Grey blocks = model weightsDiscs = side modelsGreen liquid = KV cacheRed beacon = won't loadNeedles = watts, fan, tok/sHome AI box assembly jig. The tank is GPU memory: grey blocks are the model, discs are helpers, green liquid is each person's memory. Overflow spills to the RAM tray.An always-on AI box is a resident model plan that must fit in GPU memory all at once: the chat or agent model, an embedding model for search, speech-to-text and text-to-speech for voice, maybe a vision model, plus KV cache for every session the household runs at once. Gemma 3 27B at about 4.5 bits is ≈ 15 GB of weights alone, so a 16 GB card holds it only at lower bits and short context; 24 GB is comfortable; a 128 GB DGX Spark holds a 120B MoE but reads memory at 273 GB/s, so it generates more slowly than a 5090 at 1,792 GB/s. What does not fit spills into system RAM (dual-channel DDR5, 89.6 GB/s) and every token waits on it. Then the box has to live in your home 24/7: idle watts dominate the bill, load watts become heat and fan noise. Decode speed assumes 70% of peak bandwidth; the wattmeter assumes 2 busy hours per session per day. Prices are approximate US street prices from Aug–Oct 2026, during the memory shortage; the Oki Home ($2,299) and Ghost Core ($3,499) presets copy those products' published specs. The weights are drawn as eight blocks, one per eighth of the layers; discs are the side models (embed, speech-in, voice-out, vision) and dark rings the OS and runtime; the green liquid is one KV layer per household session. When the plan overflows the tank, the top blocks (the last layers) are lifted out into the RAM tray, split at the exact number of GB that spills; when the plan won't load, all eight wait on the loading dock behind a closed gate and a red beacon, and the tank holds only the OS reserve, side models, runtime and KV. A stack too tall for its tray or dock is drawn squeezed.