Stacionarūs Kompiuteriai | LENOVO ThinkStation PGX Grace Blackwell GB10/128GB/2TBSSD/DGX OS TopSeller

Prekė gali skirtis nuo pavaizduotos paveikslėlyje, taip pat paveikslėlyje gali būti dalių, kurių nėra prekės komplektacijoje.

Prekės kodas: #1896286
6886.06€
Aprašymas

"Lenovo ThinkStation PGX. Processor model: GB10. Internal memory: 128 GB, Internal memory type: LPDDR5x-SDRAM. Total storage capacity: 2 TB, Storage media: SSD. On-board graphics card model: NVIDIA Blackwell. Wi-Fi. Operating system installed: DGX OS. Power supply: 240 W. Chassis type: Mini Tower. Product type: Mini PC. Weight: 1.2 kg. Product colour: Black"\n"SCALABLE AI DEVELOPMENT
AI Power, Perfectly Packaged


The Lenovo ThinkStation PGX small form factor, powered by the NVIDIA GB10 Grace Blackwell Superchip, enables simplified AI workflows right at your desk. It comes preloaded with the NVIDIA AI software stack and seamlessly integrates with your workstation for on-device AI development, eliminating the complexity and cost of cloud-based solutions.

AI EXCELLENCE
Big Models, Small Chip, Limitless Potential


The NVIDIA GB10 Grace Blackwell Superchip combines cutting-edge graphics with a powerful multicore ARM CPU to deliver an energy efficient system-on-a-chip (SOC) solution. It’s built to handle complex AI tasks and massive datasets with incredible speed and efficiency, making it perfect for tackling demanding workloads locally.

FULL-STACK NVIDIA AI PLATFORM
Ready-to Go AI Development Environment


A compact entry point to advanced AI, the ThinkStation PGX is preloaded with the NVIDIA DGX™ OS and NVIDIA AI software stack, providing an optimized space for AI model development. With tools like PyTorch and Jupyter® Notebooks, engineers can easily prototype, fine-tune, and inference models for smooth deployment to data center or cloud platforms.

SANDBOXED DEVELOPMENT ENVIRONMENT
Your AI Playground: Experiment. Build. Succeed.


The ThinkStation PGX workstation offers developers a secure sandbox for prototyping AI models, freeing up cluster resources for production workloads. This streamlines workflows, keeps IP on-premises, and reduces security risks — ideal for experimentation without compromising enterprise standards.

Specifications may vary depending upon region / model."

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