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NVIDIA (CHIX:NVDD) Gross-Profit-to-Asset % : 115.22% (As of Oct. 2024)


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What is NVIDIA Gross-Profit-to-Asset %?

Gross-Profit-to-Asset % is calculated as Gross Profit divided by its average Total Assets over a certain period of time. NVIDIA's annualized Gross Profit for the quarter that ended in Oct. 2024 was €96,045 Mil. NVIDIA's average Total Assets over the quarter that ended in Oct. 2024 was €83,360 Mil. Therefore, NVIDIA's annualized Gross-Profit-to-Asset % for the quarter that ended in Oct. 2024 was 115.22%.


NVIDIA Gross-Profit-to-Asset % Historical Data

The historical data trend for NVIDIA's Gross-Profit-to-Asset % 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 Gross-Profit-to-Asset % Chart

NVIDIA Annual Data
Trend Jan15 Jan16 Jan17 Jan18 Jan19 Jan20 Jan21 Jan22 Jan23 Jan24
Gross-Profit-to-Asset %
Get a 7-Day Free Trial Premium Member Only Premium Member Only 44.76 43.50 49.28 36.88 82.53

NVIDIA Quarterly Data
Jan20 Apr20 Jul20 Oct20 Jan21 Apr21 Jul21 Oct21 Jan22 Apr22 Jul22 Oct22 Jan23 Apr23 Jul23 Oct23 Jan24 Apr24 Jul24 Oct24
Gross-Profit-to-Asset % Get a 7-Day Free Trial Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only Premium Member Only 105.66 110.48 115.12 110.70 115.22

Competitive Comparison of NVIDIA's Gross-Profit-to-Asset %

For the Semiconductors subindustry, NVIDIA's Gross-Profit-to-Asset %, along with its competitors' market caps and Gross-Profit-to-Asset % data, can be viewed below:

* Competitive companies are chosen from companies within the same industry, with headquarter located in same country, with closest market capitalization; x-axis shows the market cap, and y-axis shows the term value; the bigger the dot, the larger the market cap. Note that "N/A" values will not show up in the chart.


NVIDIA's Gross-Profit-to-Asset % Distribution in the Semiconductors Industry

For the Semiconductors industry and Technology sector, NVIDIA's Gross-Profit-to-Asset % distribution charts can be found below:

* The bar in red indicates where NVIDIA's Gross-Profit-to-Asset % falls into.



NVIDIA Gross-Profit-to-Asset % Calculation

NVIDIA's annualized Gross-Profit-to-Asset % for the fiscal year that ended in Jan. 2024 is calculated as:

Gross-Profit-to-Asset %=Gross Profit (A: Jan. 2024 )/( (Total Assets (A: Jan. 2023 )+Total Assets (A: Jan. 2024 ))/ count )
=40668.318/( (38216.896+60338.304)/ 2 )
=40668.318/49277.6
=82.53 %

NVIDIA's annualized Gross-Profit-to-Asset % for the quarter that ended in Oct. 2024 is calculated as:

Gross-Profit-to-Asset %=Gross Profit (Q: Oct. 2024 )/( (Total Assets (Q: Jul. 2024 )+Total Assets (Q: Oct. 2024 ))/ count )
=96044.832/( (78579.294+88139.934)/ 2 )
=96044.832/83359.614
=115.22 %

* 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.

In the calculation of annual Gross-Profit-to-Asset %, the Gross Profit of the last fiscal year and the average total assets over the fiscal year are used. In calculating the quarterly data, the Gross Profit data used here is four times the quarterly (Oct. 2024) data. Gross-Profit-to-Asset % is displayed in the 30-year financial page.


NVIDIA Gross-Profit-to-Asset % Related Terms

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NVIDIA Business Description

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