NEXT-GEN ENTERPRISE HARDWARE

Ultimate Workstation Architecture

Powering the future of Local Machine Learning, AI Development, and Enterprise Computing at Shweta Computers.

Enterprise Components (Available by Order)

Workstation Processor

AMD Ryzen Threadripper PRO 9975WX Workstation Processor - Shweta Computers

The definitive computational backbone for heavy multi-threaded development, deep learning compilations, and relentless simulation workloads.

Core Configuration	32 Cores / 64 Threads
Clock Speed	4.0 GHz Base / 5.4 GHz Boost
PCIe Lanes	128 PCIe 5.0 Lanes (144 Total)
TDP Wattage	350W
Total Cache	160 MB (128MB L3 + 32MB L2)
Architecture	Zen 5 (4nm Platform)
Memory Support	8-Channel DDR5-6400 ECC RDIMM
Socket Type	sTR5 (WRX90 Chipset Opt.)

Visual & AI Computing

NVIDIA RTX PRO 6000 Blackwell Workstation Edition (96GB GDDR7) - Shweta Computers

Engineered specifically for training massive LLMs, complex generative AI, and rendering massive datasets locally without hardware scaling bottlenecks.

VRAM Capacity	96GB GDDR7 with ECC
Memory Bandwidth	512-bit / Up to 1,792 GB/s
CUDA Cores	24,064 Parallel Cores
Tensor AI Cores	5th Generation (FP4 Capable)
Compute Power	~4,000 AI TOPS
TDP Wattage	600W Max Board Power
Interface Type	PCIe 5.0 x16
Display Outputs	4x DisplayPort 2.1b

PRE-CONFIGURED SYSTEM SPECIFICATION

Shweta Computers Custom AI Workstation: Threadripper 9975WX & RTX 6000 Blackwell

Stop piecing loose hardware components together. Our signature Turnkey Custom AI Workstation is meticulously assembled, tuned, and verified locally by our engineers for enterprise-level Machine Learning, Deep Learning operations, LLM fine-tuning, and compute-dense industrial workflows.

System Configuration Blueprint

Processor (CPU) AMD Ryzen Threadripper PRO 9975WX (Zen 5 Platform, 32 Cores, 64 Threads, 128 PCIe 5.0 Lanes)

Graphics (GPU) NVIDIA RTX PRO 6000 Blackwell Workstation Edition (96GB GDDR7 Dedicated VRAM, 24,064 CUDA Cores)

Bus Infrastructure Direct CPU-to-GPU Link via Gen 5 x16 bandwidth rails for massive data tensor processing

System Power Supply Dual-Input Enterprise Wattage Infrastructure (Engineered for sustained 950W+ combined hardware loads)

Primary Optimization Focus Local Machine Learning Frameworks, Large Language Model (LLM) Fine-Tuning (~70B parameters), Data Science Environments