---
product_id: 404049081
title: "nVidia Tesla K80"
brand: "fujitsu"
price: "$8566"
currency: MXN
in_stock: true
reviews_count: 8
category: "Fujitsu"
url: https://www.desertcart.mx/products/404049081-nvidia-tesla-k80
store_origin: MX
region: Mexico
---

# 4992 CUDA Cores 24GB Memory Dual GPU Power nVidia Tesla K80

**Brand:** fujitsu
**Price:** $8566
**Availability:** ✅ In Stock

## Summary

> 🚀 Elevate Your Computing Game!

## Quick Answers

- **What is this?** nVidia Tesla K80 by fujitsu
- **How much does it cost?** $8566 with free shipping
- **Is it available?** Yes, in stock and ready to ship
- **Where can I buy it?** [www.desertcart.mx](https://www.desertcart.mx/products/404049081-nvidia-tesla-k80)

## Best For

- fujitsu enthusiasts

## Why This Product

- Trusted fujitsu brand quality
- Free international shipping included
- Worldwide delivery with tracking
- 15-day hassle-free returns

## Key Features

- • **Dual GPU Architecture:** Harness the power of 2x GK120 GPUs for unparalleled computational efficiency.
- • **Massive Memory Capacity:** Equipped with 24GB of GDDR5 memory for handling the most demanding tasks.
- • **Future-Proof Your Workstation:** Stay ahead of the curve with cutting-edge technology that meets the needs of tomorrow.
- • **Unleash Unmatched Performance:** Experience a staggering 5-10x boost in key application performance.
- • **Optimized for Advanced Applications:** Perfectly designed for high-performance computing tasks like STAC-A2 and Quantum Espresso.

## Overview

The nVidia Tesla K80 is a high-performance GPU designed for advanced computing tasks, featuring 24GB of GDDR5 memory and 4992 CUDA cores across dual GK120 GPUs, delivering exceptional performance boosts for a variety of demanding applications.

## Description

nVIDIA 24GB Tesla K80 Gpu Accelerator For Servers 900-22080-0002-000

Review: Great for simulations and intense math calculations - Before I get into the review itself, note that this card is intended for servers and datacenters, and requires an extensive cooling system. In particular, the K80 is passively cooled, and thus, doesn't have any fans built into it. However, it IS possible to use it in a normal desktop, though such usage is not supported by Nvidia. The motherboard and CPU I used are the Asus X99 Pro and the i7 5820k. You must enable the "Above 4G Decoding" option in the Boot menu in BIOS for the K80 to be recognized. Cooling was tricky; I 3d printed a duct with ABS+ from a 240CFM fan which is admittedly quite noisy, but the K80 is stable at 67C at full load. If you're going to go for a custom solution like ours with a 3d printer, make sure you're not using PLA as the glass transition temperature is 60-65C. Now for the actual review... We use our K80 for simulations and for deep learning. With deep learning, you're probably better off with 2 (or maybe even 4) Titan Xs as a single one of those has nearly as much single precision floating point performance as the K80. However, for use cases which require double precision, the K80 blows the Titan X out of the water. We've been very happy here with the K80, but if you're going to use a K80, you're going to be better off buying it from a vendor who has already built it into a system.
Review: Received 2x HP Pulls - one shorted my board - I ordered two of these... they were marked as HP pulls when I got them and when I attempted to install them individually to test, one shorted my board. Super unhappy w/ the experience. Returning both and ordering something else.

## Technical Specifications

| Specification | Value |
|---------------|-------|
| ASIN | B013HRQ1GO |
| Antenna Location | Professional |
| Best Sellers Rank | #2,167 in Computer Graphics Cards |
| Brand | Fujitsu |
| Compatible Devices | Desktop |
| Customer Reviews | 3.3 out of 5 stars 45 Reviews |
| Display Resolution Maximum | 4096x2160 |
| Global Trade Identification Number | 04053026870887 |
| Graphics Card Interface | PCI Express |
| Graphics Card Ram | 24 GB |
| Graphics Coprocessor | Nvidia Tesla |
| Graphics Description | Nvidia Tesla K80 |
| Graphics Processor Manufacturer | NVIDIA |
| Graphics RAM Type | GDDR5 |
| Graphics Ram Size | 24 GB |
| Graphics Ram Type | GDDR5 |
| Manufacturer | nVidia |
| Memory Clock Speed | 2500 MHz |
| Model Name | Tesla K80 |
| UPC | 885782537346 |
| Video Output Interface | DisplayPort , DVI |
| Video Processor | NVIDIA |

## Product Details

- **Brand:** Fujitsu
- **Graphics Coprocessor:** Nvidia Tesla
- **Graphics Processor Manufacturer:** NVIDIA
- **Graphics Ram Size:** 24 GB
- **Video Output Interface:** DisplayPort, DVI

## Images

![nVidia Tesla K80 - Image 1](https://m.media-amazon.com/images/I/81QPzaTLkOL.jpg)
![nVidia Tesla K80 - Image 2](https://m.media-amazon.com/images/I/91XBDvSc8UL.jpg)

## Customer Reviews

### ⭐⭐⭐⭐⭐ Great for simulations and intense math calculations
*by K***R on February 17, 2016*

Before I get into the review itself, note that this card is intended for servers and datacenters, and requires an extensive cooling system. In particular, the K80 is passively cooled, and thus, doesn't have any fans built into it. However, it IS possible to use it in a normal desktop, though such usage is not supported by Nvidia. The motherboard and CPU I used are the Asus X99 Pro and the i7 5820k. You must enable the "Above 4G Decoding" option in the Boot menu in BIOS for the K80 to be recognized. Cooling was tricky; I 3d printed a duct with ABS+ from a 240CFM fan which is admittedly quite noisy, but the K80 is stable at 67C at full load. If you're going to go for a custom solution like ours with a 3d printer, make sure you're not using PLA as the glass transition temperature is 60-65C. Now for the actual review... We use our K80 for simulations and for deep learning. With deep learning, you're probably better off with 2 (or maybe even 4) Titan Xs as a single one of those has nearly as much single precision floating point performance as the K80. However, for use cases which require double precision, the K80 blows the Titan X out of the water. We've been very happy here with the K80, but if you're going to use a K80, you're going to be better off buying it from a vendor who has already built it into a system.

### ⭐ Received 2x HP Pulls - one shorted my board
*by P***V on November 19, 2021*

I ordered two of these... they were marked as HP pulls when I got them and when I attempted to install them individually to test, one shorted my board. Super unhappy w/ the experience. Returning both and ordering something else.

### ⭐⭐⭐ Overpriced and part bent on delivery
*by D***. on January 31, 2022*

The metal mount that was attached to the GPU came bent. This suggests to me that whoever was removing them from the previous server stack was doing this in haste. Also this suggests that the GPU being on a server stack was probably excessively used before we get it. This model of GPU is at its end of life both in support of drivers and its performance (being excessively used already), however the price (at $300 when I bought it and now $400) simply does not reflect this. $200 seems more reasonable (or lower) given these facts together with the fact that you can use google's k80s for free (within limits) or for a small fee (for unlimited use). For all these reasons, together with the compromised mount I rated a 3.

## Frequently Bought Together

- nVidia Tesla K80
- COMeap NVIDIA Graphics Card Power Cable 030-0571-000 CPU 8 Pin Male to Dual PCIe 8 Pin Female Adapter for Tesla K80/M40/M60/P40/P100 4 inches (2-Pack) (10cm)
- GinTai Graphics Card Power Cable 030-0571-000 CPU 8 (Pin) Male to Dual PCIe 8 P-in Female Adapter for Tesla K80/M40/M60/P40/P100 4-inch(10cm)

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*Product available on Desertcart Mexico*
*Store origin: MX*
*Last updated: 2026-02-27*