What it is

The AI Compute Mini Host is our entry into local AI hardware: a compact desktop unit built around a unified-memory processor, designed to load and run large language models on-premise — no cloud dependency, full data control. It extends the SZO product family from signage and office computing into the AI era.

This page is intentionally early. The product is in active development, and we are publishing our direction now so that partners can shape it with us. If you are sourcing AI hardware for your market, talk to us before the spec is frozen.

Why now: the PC is being reinvented

In June 2026, NVIDIA and Microsoft used Computex and Build to declare what they called the first reinvention of the personal computer in forty years — a new class of machine, led by chips like NVIDIA's RTX Spark, built to run AI agents and large models locally rather than in the cloud. The headline products are premium consumer laptops from the big brands. But the shift they signal is much broader: over the next few years, a large share of the world's installed base of "pre-AI" computers will be replaced by machines that can run AI on-device.

That replacement wave is the opportunity — and it is not only laptops. Businesses, integrators, and public-sector buyers need something the flagship consumer laptops do not address: a compact, on-premise AI host they can place in an office, a branch, or a kiosk; run their own models on; keep their data inside; and, for resellers, put their own brand on. That is the gap the AI Compute Mini Host is built for.

Comparison showing what flagship AI laptops cover versus the B2B gap they leave: on-premise inference, fixed-location boxes, white-label hardware, and emerging markets

The flagship AI PC launches cover consumers and creators — the on-premise B2B box is the gap we build for.

Our position is deliberately practical. We are not trying to out-brand NVIDIA or Dell on a consumer laptop. We build the B2B box the big launches skip — white-labelable, configurable, sourced for your market and compliance needs — and we back it with a Shenzhen / Pearl River Delta supply chain that can move on whatever the next twelve months bring.

Platform: we source the right chip for your market

There is no single "correct" processor for local AI — it depends on your market, your compliance situation, and your budget. Rather than lock the product to one silicon vendor, we treat platform choice as a sourcing decision we make with you:

High-performance x86 (AMD Strix Halo class) — strongest model compatibility and raw performance, best for compliant markets in the Gulf, Southeast Asia, and Latin America.
Domestic / unrestricted-supply chips — for buyers in Russia, the CIS, and other markets where export-controlled silicon is impractical, or where supply-chain independence is a procurement requirement.
Arm-based unified-memory platforms — as the new AI-PC chip class matures, we track it and source from it where it fits.

Three chip platforms matched to markets: high-performance x86 for compliant markets, domestic unrestricted chips for Russia and restricted markets, and Arm unified-memory as the rising class

We match the platform to your market and compliance situation — not the other way around.

Because we operate inside one of the world's deepest electronics supply ecosystems, "which chip" is a conversation, not a constraint. Tell us the market and the workload; we propose the platform.

Target specifications (roadmap)

Final specifications are being defined with launch partners. Our target configuration:

Architecture

Unified memory (shared CPU/GPU pool)

Unified memory

Up to 128 GB LPDDR5X

Model capacity

Local LLMs up to ~120B params

Form factor

Mac-mini class · desktop compact

Platform options

AMD Strix Halo · domestic-chip variant

Branding

SZO or full white-label (50+ units)

Diagram of unified memory architecture used in the AI compute mini host

The unified-memory architecture at the core of the design — one large shared memory pool lets the whole model fit on a single small device.

Who it is for

On-premise AI for privacy-sensitive sectors — finance, healthcare, government, and any organisation that cannot send data to the cloud.
Regions with limited or costly cloud access — local inference where reliable cloud AI is not a given.
Resellers and system integrators — white-label AI hardware for your own brand and market.
Edge and vertical applications — kiosks, on-site assistants, document processing, and retrieval systems.

How much memory do you actually need?

Memory capacity decides which models you can run. Most business workloads sit comfortably within a single 128 GB host.

Chart of memory needed by AI model size with 128GB ceiling

Approximate memory by model size (4-bit). A 128 GB host covers the range most businesses need.

Register early interest

We are talking to OEM/ODM partners and pilot customers now. Tell us your target market, model sizes, and volume — we will share our roadmap and discuss a configuration that fits. No obligation.

Request early quote →

Why source this from ShenzhenOPS

We are a Shenzhen manufacturer with an existing export footprint across Russia & CIS, the Middle East, Southeast Asia, and Latin America. That means certified products (CE, FCC, EAC), white-label terms, and local-market support — applied to a new product class. We are honest about the trade-offs of unified-memory hardware (see our explainer on unified memory) and we build to the questions serious buyers ask.

AI Compute Mini Host