Everything you’ve seen from us — Aillex’s cloned voice, her 26-billion-parameter brain, the 3D avatar, the videos that produce themselves every morning at 7am — runs on one computer. Not a server rack. Not a cloud account. A prebuilt gaming PC sitting in a home office.
This is that machine, and an honest breakdown of what matters.
The exact build
An iBUYPOWER prebuilt — the RDY Y70 TI B05:
| Part | Spec |
|---|---|
| GPU | GeForce RTX 5090 — 32 GB GDDR7 |
| CPU | Intel Core i9-14900KF (24 cores) |
| RAM | 64 GB DDR5-6000 |
| Storage | 4 TB NVMe Gen4 SSD |
| PSU | 1000 W Corsair RM1000e (Gold, fully modular) |
| Board | MSI PRO Z790-P WiFi |
| Cooling | 360 mm AIO liquid cooler |
| Case | HYTE Y70 Touch Infinite |
| OS | Windows 11 Home (+ WSL2 Ubuntu) |
What actually matters for local AI (ranked)
1. VRAM is the whole game — 32 GB of it. Every capability on this site is ultimately a VRAM budget line: the 26B brain (~17.6 GB), speech recognition (~1.5 GB), real-time lip-sync (~8.5 GB). They run simultaneously because 32 GB gives room to co-resident models. With 16 GB you’d run a smaller brain OR the avatar — not both. If you take one thing from this article: buy VRAM, not framerate.
2. System RAM — 64 GB is the quiet hero. WSL2, model conversion, video pipelines, a dozen Python environments — we routinely sit above 40 GB. 32 GB works; 64 GB removes a whole class of mystery failures.
3. Storage — 4 TB fills faster than you think. Models are huge: our LoRA library, three video generators, TTS models and checkpoints currently occupy well over a terabyte. Gen4 speed matters less than capacity — models load once and stay warm.
4. The 1000 W PSU earns its keep. A 5090 under sustained video-generation load is not a gaming duty cycle. Generation runs hammer the card for 40–60 minutes flat. Headroom = stability.
5. CPU matters less than you’d expect — with one exception. Inference lives on the GPU. But our text-to-speech runs entirely on CPU (that story here) precisely to keep VRAM free — and the 24-core i9 doesn’t blink at it.
Honest notes on prebuilt vs self-built
We didn’t plan an “AI workstation.” This was bought as a gaming PC — the AI obsession came after. That’s actually the point: the machine you may already own (or can order assembled) is enough. No used datacenter cards, no Threadripper tax. One warranty, one box, GPU arrives packaged separately (install it yourself — it’s four screws and a cable).
Could you part-pick the same spec cheaper? Somewhat. Would we trade the 3-year warranty and the working-out-of-the-box on a machine that now runs a 7am production pipeline unattended? No.
Considering a build? Our referral link is here — it supports the channel at no cost to you.
What we’d change (2026 edition)
- More VRAM, always — if a 48 GB consumer card existed at sane pricing, we’d own it. Watch this space.
- Second SSD from day one. You will fill the first one.
- Everything else? This box has rendered thousands of images, hundreds of video clips, and an entire self-producing YouTube channel without a single hardware complaint.
What it runs: the full local AI companion architecture →
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