• Новая видеокарта RTX 5880 Ada Generation 48 ГБ — модернизированная версия RTX 6000 Ada для профессионального обучения ИИ
  • New RTX 5880 Ada Generation 48GB - A streamlined version of the RTX 6000 Ada for professional AI training
  • New RTX 5880 Ada Generation 48GB - A streamlined version of the RTX 6000 Ada for professional AI training
  • New RTX 5880 Ada Generation 48GB - A streamlined version of the RTX 6000 Ada for professional AI training
  • New RTX 5880 Ada Generation 48GB - A streamlined version of the RTX 6000 Ada for professional AI training
  • Новая видеокарта RTX 5880 Ada Generation 48 ГБ — модернизированная версия RTX 6000 Ada для профессионального обучения ИИ
  • New RTX 5880 Ada Generation 48GB - A streamlined version of the RTX 6000 Ada for professional AI training
  • New RTX 5880 Ada Generation 48GB - A streamlined version of the RTX 6000 Ada for professional AI training
  • New RTX 5880 Ada Generation 48GB - A streamlined version of the RTX 6000 Ada for professional AI training
  • New RTX 5880 Ada Generation 48GB - A streamlined version of the RTX 6000 Ada for professional AI training

New RTX 5880 Ada Generation 48GB - A streamlined version of the RTX 6000 Ada for professional AI training

No.RTX 5880
  • GPU Model: Based on the specifications, this is a professional workstation card, likely a variant of the NVIDIA RTX 6000 Ada Generation.

  • Form Factor: A slimmer version compared to the standard RTX 6000 Ada.

Performance & Core Architecture

  • CUDA Cores: 4,608

  • NV Tensor Cores: 576

  • RT Cores: 72

  • RTX OPS: 84 Trillion (84T)

  • FP32 Performance: 16.3 TFLOPS

  • GPU Process: 14 nanometers

Memory

  • GPU Memory: 48 GB GDDR6

  • Video Memory Speed: 2 ns

  • Memory Interface: 384-Bit

  • Video Memory Bandwidth: 960 GB/s

Clock & Power

  • Core Clock: 532 MHz (Base)

  • Memory Clock: Not Specified

  • Max Power Consumption: 295 W

Interface & Connectivity

  • Graphics Bus: PCI Express 4.0 (Backwards compatible with PCIe 3.0 x16)

  • Interface Type: PCI

  • Output Interface: DVI

  • VR Support: Yes

  • Новая видеокарта RTX 5880 Ada Generation 48 ГБ — модернизированная версия RTX 6000 Ada для профессионального обучения ИИ
  • New RTX 5880 Ada Generation 48GB - A streamlined version of the RTX 6000 Ada for professional AI training
  • New RTX 5880 Ada Generation 48GB - A streamlined version of the RTX 6000 Ada for professional AI training
  • New RTX 5880 Ada Generation 48GB - A streamlined version of the RTX 6000 Ada for professional AI training
  • New RTX 5880 Ada Generation 48GB - A streamlined version of the RTX 6000 Ada for professional AI training
  • Description
  • Ordering & Payment Terms

Product Overview

This graphics card is a slimmer version of the high-end RTX 6000 Ada. While it features a reduced core count (CUDA, Tensor, and RT Cores) and a 24% lower single-precision floating-point performance compared to the full RTX 6000 Ada, it remains a powerful solution for demanding professional workflows. It is well-suited for handling large datasets, complex 3D rendering, data science, and simulation workloads.

The NVRTX 5880 Ada is a workstation graphics card from Nvidia that is targeted at consumer and professional areas such as AI training

CUDA Parallel-Processing Cores
4,608
NVTensor Cores
576
NV RT Cores
72
GPU Memory
48GB GDDR6
RTX-OPS
84T
Rays Cast
10 Giga Rays/Sec
FP32 Performance
16.3 TFLOPS

Ordering & Payment Terms:

  • Minimum Order Quantity (MOQ): Flexible for small orders
  • Shipping: DDP (Delivered Duty Paid) to your destination or shipment via your designated courier account.
  • Payment Method: T/T (Bank Transfer)
  • Payment Terms:
    30% advance payment, with 70% balance due prior to shipment for bulk orders


BANK INFORMATION

Bank Name: DBS BANK (HONG KONG) LIMITED
Account Name: Shenzhen VAN Electronics Co., Ltd.
Account No.: 798 291 1671
Bank Address: 11th Floor, The Center, 99 Queen's Road Central, Central, Hong Kong
Swift Code: DHBKHKHH

Contact for Quotation:
Kindly email your requirements to sales@szvan.com for a customized quotation and optimal solution.
Attn: Jessica Lee

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