NVIDIA Quadro RTX 8000
Accelerators

NVIDIA Quadro RTX 8000

Viperatech

Overview

The NVIDIA Quadro RTX 8000 is the Turing-generation professional flagship with 48GB GDDR6 ECC, 4,608 CUDA cores, and 576 Tensor Cores at 295W. NVLink support allows two cards to pool 96GB of memory. With 130.5 TFLOPS Tensor performance and proven Quadro enterprise certification, it provides strong large-model AI capacity at a competitive price vs current-generation Ada cards.

Key Features

  • 48GB GDDR6 ECC with NVLink for 96GB dual-card configuration
  • Turing architecture: 4,608 CUDA + 576 Tensor Cores
  • 130.5 TFLOPS Tensor and 16.3 TFLOPS FP32 performance
  • 672 GB/s memory bandwidth at 295W TDP
  • Proven Quadro enterprise driver stability and ISV certification

Ideal For

AI researchers and enterprise teams needing cost-effective 48GB VRAM (or NVLink-scaled 96GB) for large model inference and training on a mature professional GPU platform.

Specification

Detail

GPU Architecture

Turing

CUDA Parallel Processing cores

4608

NVIDIA Tensor Cores

576

NVIDIA RT Cores

72

Frame Buffer Memory

48 GB GDDR6

RTX-OPS

84T

Rays Cast

10 Giga Rays/Sec

Peak Single Precision (FP32) Performance

16.3 TFLOPS

Peak Half Precision (FP16) Performance

32.6 TFLOPS

Peak Integer Operation (INT8) Performance

65.2 TOPS

Deep Learning TeraFLOPS^1

130.5 Tensor TFLOPS

Memory Interface

384-bit

Memory Bandwidth

672 GB/s

Max Power Consumption

295 W

Graphics Bus

PCI Express 3.0 x16

Display Connectors

DP 1.4 (4) + VirtualLink (1)

Form Factor

4.4” H x 10.5” L Dual Slot

Product Weight

1.002 kg

Thermal Solution

Active

Power Connector

1x 8-pin & 1x 6-pin

Frame lock

Compatible (with Quadro Sync II)

NVLink Interconnect

100 GB/s

$4,915.00

Prices may vary. Verify on vendor site.

View on Viperatech →

Quick Specs

Specification
Detail
GPU Architecture
Turing
CUDA Parallel Processing cores
4608
NVIDIA Tensor Cores
576
NVIDIA RT Cores
72
Frame Buffer Memory
48 GB GDDR6

Tags

llm-inferencellm-traininggenerative-aicomputer-visionsimulationsmall-modelmedium-model