Workstation Lenovo ThinkStation PGX 30KL MT – 1×GB10 Grace Blackwell Superchip, 128 GB RAM, 1 TB NVMe SSD, NVIDIA Blackwell, Wi‑Fi 6/7, Bluetooth 5.3, 10GbE

Lenovo ThinkStation PGX 30KL MT is a mid-tower workstation configured with a single GB10 Grace Blackwell Superchip, 128 GB of system memory and a 1 TB NVMe SED SSD. Designed for compute-heavy workflows, the system supports NVIDIA Blackwell GPU acceleration and ships with NVIDIA DGX Base OS. Integrated 10GbE networking, Wi‑Fi 6/7 and Bluetooth 5.3 provide high-speed connectivity for data transfers and collaboration. The chassis and cooling architecture are engineered to sustain prolonged high-load operation typical for AI development, data science and visualization tasks.

Advantages

The workstation combines a powerful Grace Blackwell Superchip with large memory capacity to handle large models and datasets in memory. NVIDIA Blackwell GPU support enables accelerated training and inference, while the NVMe SED SSD delivers fast, encrypted storage for active projects. Onboard 10GbE and modern wireless options reduce network bottlenecks, and the preinstalled NVIDIA DGX Base OS simplifies deployment of AI frameworks and tooling. The mid-tower form factor balances expandability and footprint for office or lab environments.

Suitable for

• AI model development, training and inference
• Data science, analytics and large-scale dataset processing
• 3D rendering, visualization and GPU-accelerated simulations
• High-performance compute tasks and software development requiring large memory

Key specifications

• Processor: single GB10 Grace Blackwell Superchip
• System memory: 128 GB RAM
• Primary storage: 1 TB NVMe SED SSD (hardware encrypted)
• GPU: supports NVIDIA Blackwell architecture for accelerated compute
• Networking: integrated 10GbE LAN and Wi‑Fi 6 / Wi‑Fi 7 wireless connectivity
• Wireless: Bluetooth 5.3
• Operating environment: supplied with NVIDIA DGX Base OS for AI workloads
• Form factor: mid-tower workstation with expanded cooling and expansion slots

How to use

Install the workstation in a well-ventilated area and connect required peripherals and network links. Use the included NVIDIA DGX Base OS to provision AI frameworks, drivers and container runtimes; configure GPU drivers and CUDA-compatible toolchains as needed for your software stack. Allocate memory and storage resources according to project requirements and use the 10GbE or Wi‑Fi 6/7 interfaces for high-speed data transfer. For encrypted workflows, enable and manage the SSD's self-encrypting features through the system management utilities.

Recommendations

For sustained heavy workloads, ensure adequate cooling and clean airflow paths. Keep GPU and system firmware up to date and use supported drivers from NVIDIA for best performance. When working with sensitive datasets, enable the SSD’s hardware encryption and follow organizational security policies. Consider network configuration and storage-tiering to optimize dataset staging and long-term archival.