2026 Next-Gen AI Compute Platform

Complete AI Compute Infrastructure
Solutions

From single-GPU workstations to thousand-card AI clusters, NEXUS delivers design, deployment, tuning and operations as one integrated service — a reliable compute foundation for LLM training, machine vision, autonomous driving simulation and smart cities.

Compute Density per Cluster
200+AI Projects Delivered
99.9%Cluster Availability
7×24Expert Support
Solutions

AI Compute Hardware for Every Scenario

Covering training, inference and edge computing, with standard products and deep customization across NVIDIA and domestic chip platforms.

AI Training Servers

High-density 8U/8-GPU and 4U/4-GPU training nodes with NVLink interconnect and lossless high-speed networking for trillion-parameter model training.

NVIDIA H / B Series · Domestic Chips

AI Compute Clusters

Thousand-card RoCE / InfiniBand cluster solutions with intelligent scheduling and container orchestration — train-and-inference integration out of the box.

Up to 2,048 GPUs per Cluster

Edge AI Boxes

Industrial-grade wide-temperature design with 8–200 TOPS options for real-time inference in manufacturing inspection, security patrol and vehicle-road coordination.

IP40 · -20℃ ~ 60℃

Liquid Cooling Systems

Cold-plate and immersion cooling solutions with PUE as low as 1.08 and up to 100kW per rack — the first choice for green AI data centers.

PUE 1.08 · 100kW / Rack

GPU Workstations

Desktop compute for LLM fine-tuning, graphics rendering and scientific computing, with quiet design and flexible 1–4 GPU configurations.

Full RTX Lineup · Quiet Cooling

All-Flash Parallel Storage

GPU Direct Storage-ready parallel file systems with 25GB/s single-stream bandwidth to eliminate training data bottlenecks.

25GB/s Single-Stream Bandwidth
Why NEXUS

Turning Compute Delivery into Measurable Business Outcomes

Factory-Verified Delivery

72-hour stress testing and full-pipeline performance baselining before shipment — delivered performance matches spec.

Application-Level Tuning

PyTorch / TensorFlow framework-level optimization lifts training throughput 15–30% on average.

Vendor-Level Support

Joint chip-vendor certification and a spare-parts system, with key components on site within 4 hours.

Full-Lifecycle Operations

Remote monitoring, fault prediction and capacity planning with 7×24 expert duty.

Use Cases

Proven at Scale in Critical Scenarios

01

LLM Training & Fine-Tuning

Thousand-card clusters for AI data centers and research institutes — end-to-end training for 10B+ parameter models with zero-loss checkpoint resume.

02

Industrial Machine Vision Inspection

Edge AI boxes plus a vision platform deliver 99.5%+ defect detection, with line retrofits completed in under 4 weeks.

03

Autonomous Driving Simulation

Multi-GPU parallel simulation with scenario libraries lifts daily simulated mileage 10× and supports closed-loop training.

04

Smart City Video Analytics

City-scale video compute foundations handling 10,000+ streams with structured analysis latency under 200ms.

Process

Four Steps to Compute Upgrade

STEP 01

Requirements Discovery

Technical consultants assess workloads, data scale and compute gaps on site, then deliver a requirements analysis report.

STEP 02

Solution Design

Architects deliver hardware selection, network topology and budget estimates within 3 working days.

STEP 03

Deployment & Delivery

Factory pre-assembled and tested systems ship as complete units; on-site deployment and acceptance testing with full visibility.

STEP 04

Operations Support

7×24 monitoring and alerts, quarterly health checks and capacity planning advice.

Get Started

Book a Custom Solution Consultation

Leave your requirements and our technical consultants will contact you within one working day with initial hardware configuration and budget guidance — free of charge.

One-on-one with senior architects — no pitching, just problem solving
A Compute Assessment & Solution Proposal within 48 hours
Trial units and benchmark comparisons before you commit

Get Your Custom Solution

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