NVIDIA (BSP:NVDC34) Inventories, Finished Goods

: R$10,122 Mil (As of Jan. 2024)

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NVIDIA's quarterly finished goods increased from Jul. 2023 (R$7,820 Mil) to Oct. 2023 (R$8,989 Mil) and increased from Oct. 2023 (R$8,989 Mil) to Jan. 2024 (R$10,122 Mil).

NVIDIA's annual finished goods increased from Jan. 2022 (R$6,205 Mil) to Jan. 2023 (R$11,750 Mil) but then declined from Jan. 2023 (R$11,750 Mil) to Jan. 2024 (R$10,122 Mil).

NVIDIA Inventories, Finished Goods Historical Data

The historical data trend for NVIDIA's Inventories, Finished Goods 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.

* Premium members only.

NVIDIA Annual Data

Trend

Jan15

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Jan21

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Jan23

Jan24

Inventories, Finished Goods

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1,930.31

3,955.70

6,204.66

11,749.95

10,121.66

NVIDIA Quarterly Data
	Apr19	Jul19	Oct19	Jan20	Apr20	Jul20	Oct20	Jan21	Apr21	Jul21	Oct21	Jan22	Apr22	Jul22	Oct22	Jan23	Apr23	Jul23	Oct23	Jan24
Inventories, Finished Goods	Get a 7-Day Free Trial															11,749.95	9,400.25	7,820.02	8,989.39	10,121.66

NVIDIA Inventories, Finished Goods Calculation

The products in a manufacturer's inventory that are completed and are waiting to be sold.

NVIDIA (BSP:NVDC34) Business Description

Industry

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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.

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