PNY NVIDIA RTX Pro 6000 Blackwell Max-Q 96GB GDDR7 24064 CUDA Cores PCI Express 5.0 x16 300W Graphics CardVCNRTXPRO6000BQ-PB
Accelerators

PNY NVIDIA RTX Pro 6000 Blackwell Max-Q 96GB GDDR7 24064 CUDA Cores PCI Express 5.0 x16 300W Graphics CardVCNRTXPRO6000BQ-PB

Central Computer

Overview

PNY NVIDIA RTX Pro 6000 Blackwell Max-Q 96GB GDDR7 24064 CUDA Cores PCI Express 5.0 x16 300W Graphics CardVCNRTXPRO6000BQ-PB is an AI accelerator card sold by Central Computer, built around RTX Pro 6000 Blackwell Max-Q with 96GB of GPU memory.

Key Features

  • GPU: RTX Pro 6000 Blackwell Max-Q
  • 96GB of GPU memory
  • 96GB system memory
  • PCI Express add-in card

Ideal For

buyers adding professional GPU capacity to a system they already own, and anyone pricing the same silicon across vendors

PNY Part Number

VCNRTXPRO6000BQ-PB

Architecture

NVIDIA Blackwell Architecture

Foundry

TSMC

Process Size

4N NVIDIA Custom Process

Transistors

92.2 Billion

Die Size

750 mm²

CUDA Parallel Processing Cores

24,064

NVIDIA Tensor Cores

752

NVIDIA RT Cores

188

Single-Precision Performance

125 TFLOPS

AI Performance

4000 AI TOPS

RT Core Performance

380 TFLOPS

GPU Memory

96 GB GDDR7 with ECC

Memory Interface

512-bit

Memory Bandwidth

1792 GB/s

Max Power Consumption

300W

Multi-Instance GPU

Up to 4x 24GB, Up to 2x 48GB, Up to 1x 96GB

Graphics Bus

PCI Express 5.0 x16

Display Connectors

DP 2.1 (4)

Form Factor

4.4” H x 10.5” L, FHFL Dual Slot

Product Weight

1.23 kg

Thermal Solution

Blower Active Fan

NVIDIA® 3D Vision® and 3D Vision Pro

Support Via 3-pin Mini DIN

Frame Lock

Compatible (with NVIDIA RTX PRO Sync)

Power Connector

1x PCIe CEM5 16-pin

NVENC | NVDEC | JPEG

4x | 4x | 4x

SKU

VGAPNYRP60QR

Brand

PNY Technology

$14,499.99

Prices may vary. Verify on vendor site.

Quick Specs

PNY Part Number
VCNRTXPRO6000BQ-PB
Architecture
NVIDIA Blackwell Architecture
Foundry
TSMC
Process Size
4N NVIDIA Custom Process
Transistors
92.2 Billion
Die Size
750 mm²

Tags

llm-inferencemodel-trainingmulti-gpuhigh-computesmall-modelmedium-modellarge-modelhigh-vram