NVIDIA (BSP:NVDC34) Institutional Ownership : 0.00% (As of Mar. 22, 2025)

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What is NVIDIA Institutional Ownership?

Institutional ownership is the percentage of shares that are owned by institutions out of the total shares outstanding. As of today, NVIDIA's institutional ownership is 0.00%.

Insider Ownership is the percentage of shares that are owned by company insiders relative to the total shares outstanding. As of today, NVIDIA's Insider Ownership is 0.00%.

Float Percentage Of Total Shares Outstanding is the percentage of float shares relative to the total shares outstanding. As of today, NVIDIA's Float Percentage Of Total Shares Outstanding is 85.38%.

NVIDIA Institutional Ownership Historical Data

The historical data trend for NVIDIA's Institutional Ownership 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 Institutional Ownership Chart

NVIDIA Historical Data

The historical data trend for NVIDIA can be seen below:

	2020-05-31	2020-06-30	2020-07-31	2021-07-31	2021-08-31	2021-09-30	2021-10-31	2021-11-30	2021-12-31	2024-08-31
Institutional Ownership	0.01	0.01	0.02	0.01	0.01	0.01	0.01	0.01	0.01	0.01

NVIDIA Institutional Ownership Calculation

The percentage of shares that are owned by institutions out of the total shares outstanding.

NVIDIA Business Description

Industry

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Address

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

Website

https://www.nvidia.com

Nvidia Corp is an upfront developer of graphics processing unit and a full-stack computing infrastructure company with data-center-scale offerings that are reshaping industry. Traditionally, GPU were used to enhanvce experience,now Nvidia offers AI GPUs, and also a software platform, Cuda, used for AI model development and training. The company is also expanding its data center networking solutions, helping to tie GPUs together to handle complex workloads. such as AI, model training and inference, data analytics, scientific computing, and 3D graphics, with vertical-specific optimizations to address industries ranging from healthcare and telecom to automotive and manufacturing.

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