Compact AI Servers
& GPU Compute

Compact AI compute products and deployment services for edge inference, industrial vision, R&D validation and on-site computing.

Define the workload first, then configure the compute

This page presents product and service categories first. Specific CPU, GPU, memory, storage, power and chassis models will be published once official product documentation is available.

Compact AI Servers

Compact server directions for space-constrained, fast-deployment and on-site computing needs.

GPU Compute Products

GPU configurations selected around inference, graphics, simulation and data processing workloads.

Edge Computing Deployment

Low-latency computing at the device side, workshop side and local machine room.

AI compute and intelligent data vision

Compact compute for industrial sites

The value of compact servers and edge devices goes beyond hardware specifications — it depends on how well they fit the site's space, power, cooling, network and workload.

Industrial vision and image processing
Local AI inference and model validation
Equipment data processing and edge applications
Submit compute requirements

What to confirm before configuration

Don't select by graphics card model alone — determine the full system configuration from the workload and deployment conditions.

RequirementInformation to provideConfiguration impact
WorkloadInference, training, graphics, simulation or data processingGPU type, memory and software environment
Models & concurrencyModel size, precision, concurrency and latency targetsCompute, memory and expansion needs
Deployment locationDesktop, rack, edge site or inside equipmentDimensions, noise, protection and cooling
Data & networkData volume, retention period and network interfacesStorage, network cards and optical interconnect configuration
Power & environmentPower conditions, temperature and continuous operating hoursPower supply, airflow and reliability design

Our AI product delivery boundaries

This first version uses no unconfirmed GPU brands, product models or performance figures; authorizations and specifications will be verified item by item before official release.

01

Workload Review

Confirm task types, model size, concurrency and latency.

02

Hardware Configuration

Select the GPU, CPU, memory, storage and networking combination.

03

Environment Adaptation

Check space, power, cooling and operating conditions.

04

Deployment Support

Provide installation, environment preparation and operational assistance.