Own your intelligence on your desk
Your private AI arrives configured
Frontier open models on hardware you own, with more under your desk than ever.
Access the whole lineup
*The eight desk boxes are the same NVIDIA GB10 Grace Blackwell platform: identical silicon, 128GB unified memory, identical throughput — they differ in chassis, storage, warranty channel and price. The two Y Towers are the tier above: RTX PRO 6000 builds, priced at order.
Read morestack, installedSee the stack
- Local model server, quantised and tuned
- OpenClaw agent runtime, wired to your tools
- A ChatGPT-style app on your own network
Models that will not fit on a laptop

DeepSeek V4 Flash · 15.5–16.6 tok/s decode · 411 tok/s read
*Throughput verified hands-on on a single DGX Spark at UD-IQ3_XXS with 131,072 tokens of context. Before your machine ships we re-run the numbers on your exact unit and hand you the results. Zero tokens leave the building because inference never touches a network.
Read moreFrontier intelligence, answering to no one
There’s a model for everything
Scores: Artificial Analysis Intelligence Index v4.1, nine independent evals. Memory figures are measured GGUF file sizes, not estimates. DeepSeek V4 Flash verified hands-on: 103GB resident, 18GB free, 131,072-token context on a single box.
Read moreWhat do you want to run on it?
All of it runs on the same machine. Pick one.
“Runs on a single DGX Spark.”
Poolside
Laguna-S-2.1 launch, on this exact hardware class
The honest version: if nothing runs while you sleep and nothing you type is sensitive, a subscription is the better deal and we will say so. The moment agents loop — or the data is not yours to share — the answer flips. Payback maths, worked through, at why-local/cost.
Token capacitymeasured every month
Set it running.Come back to done.
Run 130+
open models
Agent runs shown are from the measured build: DeepSeek V4 Flash at 16 tok/s decode sustains roughly 4.2M tokens over an eight-hour overnight loop. Your workloads will differ — which is why every install ends with your numbers, not ours.
Read moreTen builds. Two tiers.
Eight OEMs ship the same NVIDIA GB10 — 128GB unified memory, identical measured throughput, pick on chassis and price. Above them, two Y Tower builds on RTX PRO 6000 GPUs for those who need more speed or native-FP8 fidelity.
Unlock the free guide to running AI locally
Written by the people who install it — what fits in 128GB, where the payback turns, and the questions worth asking any vendor.

































