Step 1 of 6

CPU. Establish the compute foundation.

A 6-core, 12-thread processor provides the responsive compute foundation for system services, orchestration, storage operations, and everyday local AI workloads.

Step 2 of 6

Memory. Add working headroom.

Increase system memory to keep local AI services, containers, vector workloads, and multitasking responsive under sustained use.

Step 3 of 6

GPU memory. Choose your local AI capacity.

Scale GPU memory to accelerate larger models, higher-throughput inference, multimodal workloads, and concurrent AI services.

Step 4 of 6

SSD storage. Choose your system and optional drive.

Expand high-speed SSD capacity for faster model loading, vector search, scratch workloads, and sustained data-intensive AI workflows.

System SSD

SSD 2 · Optional drive

Step 5 of 6

HDD storage. Keep your data close.

High-endurance HDDs for sustained workloads, long service life, and protected RAID5 capacity. RAID storage pools are built once at deployment and cannot be upgraded or changed later.

Step 6 of 6

Networking. Move data without waiting.

Increase network bandwidth to move model files, datasets, backups, and shared AI workloads with less transfer overhead.