Hardware Profiles & Reference Builds
Class-level reference builds — appliances, workstations and servers — for sizing a private AI Business OS before picking a specific vendor device. Each is scored for local AI.
Recommended on-prem appliance
Run it on a GB10 box with AI Business OS pre-installed
The simplest way to put a private AI workforce on-premise: a compact GB10 Grace Blackwell appliance with ~128 GB unified memory — from ASUS, Dell or NVIDIA — shipped by BrainOutput with BrainOS pre-installed, so it runs your agents the day it arrives.
128GB unified · GB10 Grace Blackwell · on-prem
128GB unified · GB10 Grace Blackwell · on-prem
128GB unified · GB10 Grace Blackwell · on-prem
Other reference builds
Class-level RTX and Apple-silicon builds for sizing comparisons — useful reference points alongside the GB10 on-prem appliance above.
An 8-GPU HGX H100 server with ~640GB of aggregate HBM3 — datacenter-scale training and high-throughput serving in one node.
Dell's flagship 8-GPU AI server, configurable with H100 or H200 — a rack-scale building block for AI clusters.
A high-end workstation designed to hold multiple double-width pro GPUs — a deskside multi-GPU AI platform.
A dual-socket workstation built for multiple professional GPUs — suited to teams running heavier local AI on-prem.
Supermicro's deskside multi-GPU tower line — a flexible platform for on-prem local AI with several pro or datacenter cards.
Up to 192GB unified memory at ~800 GB/s — still one of the most memory-rich single-box options for running very large local models.
A serious local AI workstation: four RTX 4090s pool to 96GB, enough to serve flagship 70B models and run many concurrent agents privately.
A professional tower that can house large pro GPUs (e.g. RTX 6000 Ada / A6000) for serious on-desk local AI.
Up to 128GB of unified memory in a compact desktop — large enough to hold 70B-class models entirely on-device.
A compact x86 mini PC whose large unified memory (up to ~128GB) lets the integrated GPU/NPU run sizeable local models.
A workstation tuned for local coding agents: ~48GB across two 24GB cards runs strong 32B coder models and serves a small engineering team privately.
More memory bandwidth and up to 64GB unified memory make this a surprisingly capable small-form-factor local-AI box.
A confidential evidence-search box for legal teams: ~48GB hosts a strong model and large-document retrieval for a DocMatch-style workflow entirely in the firm.
A back-office box for finance teams: extracts invoices, reconciles data and drives Odoo/ERP workflows on a private 14–32B model.
A tiny, low-power mini PC with shared memory: a frugal way to run a private 7–14B assistant for a small business with almost no noise or running cost.
A tiny, near-silent desktop that runs small-to-mid LLMs on unified memory — the cheapest credible Apple on-ramp to local AI.
A budget two-GPU box: pooling two 12GB RTX 3060s gives 24GB total for bigger models or two assistants in parallel on a tight budget.
A quiet small-form-factor box for a single office: enough for a private assistant and light document RAG on a 7–14B model.
An on-site box for hospitality: runs a multilingual guest-messaging and front-desk automation agent without sending guest data to the cloud.
Turn your machine into a private AI Business OS
Run your own AI agents on hardware you control — private by design, no per-seat data leaving your premises. BrainOutput helps you pick the right machine and turn it into a working AI Business OS.