NVIDIA (BUE:NVDA) Accumulated Depreciation

: ARS-2,836,851 Mil (As of Jan. 2024)

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Note: A negative number here means the assets are depreciated. When depricates more, the absolute value gets bigger.

NVIDIA's quarterly accumulated depreciation stayed the same from Jul. 2023 (ARS0 Mil) to Oct. 2023 (ARS0 Mil) but then increased from Oct. 2023 (ARS0 Mil) to Jan. 2024 (ARS-2,836,851 Mil).

NVIDIA's annual accumulated depreciation increased from Jan. 2022 (ARS-195,400 Mil) to Jan. 2023 (ARS-476,431 Mil) and increased from Jan. 2023 (ARS-476,431 Mil) to Jan. 2024 (ARS-2,836,851 Mil).

NVIDIA Accumulated Depreciation Historical Data

The historical data trend for NVIDIA's Accumulated Depreciation can be seen below:

* For Operating Data section: All numbers are indicated by the unit behind each term and all currency related amount are in USD.
* For other sections: All numbers are in millions except for per share data, ratio, and percentage. All currency related amount are indicated in the company's associated stock exchange currency.

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NVIDIA Annual Data

Trend

Jan15

Jan16

Jan17

Jan18

Jan19

Jan20

Jan21

Jan22

Jan23

Jan24

Accumulated Depreciation

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-60,518.46

-118,384.64

-195,400.04

-476,430.79

-2,836,850.99

NVIDIA Quarterly Data
	Apr19	Jul19	Oct19	Jan20	Apr20	Jul20	Oct20	Jan21	Apr21	Jul21	Oct21	Jan22	Apr22	Jul22	Oct22	Jan23	Apr23	Jul23	Oct23	Jan24
Accumulated Depreciation	Get a 7-Day Free Trial															-476,430.79	-	-	-	-2,836,850.99

NVIDIA Accumulated Depreciation Calculation

The cumulative depreciation of an asset up to a single point in its life. Regardless of the method used to calculate it, the depreciation of an asset during a single period is added to the previous period's accumulated depreciation to get the current accumulated depreciation.

NVIDIA Accumulated Depreciation Related Terms

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NVIDIA (BUE:NVDA) Business Description

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Address

2788 San Tomas Expressway, Santa Clara, CA, USA, 95051

Website

https://www.nvidia.com

Nvidia is a leading developer of graphics processing units. Traditionally, GPUs were used to enhance the experience on computing platforms, most notably in gaming applications on PCs. GPU use cases have since emerged as important semiconductors used in artificial intelligence. Nvidia not only offers AI GPUs, but also a software platform, Cuda, used for AI model development and training. Nvidia is also expanding its data center networking solutions, helping to tie GPUs together to handle complex workloads.