NVIDIA's total inventories for the quarter that ended in Jan. 2024 was $5,282 Mil. NVIDIA's average total inventories from the quarter that ended in Oct. 2023 to the quarter that ended in Jan. 2024 was $5,031 Mil.
In Ben Graham's calculation of Net-Net Working Capital, inventory is only considered worth half of its book value. NVIDIA's Net-Net Working Capital per share for the quarter that ended in Jan. 2024 was $5.43.
Days Inventory indicates the number of days of goods in sales that a company has in the inventory.
NVIDIA's Days Inventory for the
three
months ended in Jan. 2024 was 86.41.
Inventory Turnover measures how fast the company turns over its inventory within a year.
NVIDIA's Inventory Turnover for the quarter that ended in Jan. 2024 was 1.06.
Inventory-to-Revenue determines the ability of a company to manage their inventory levels. It measures the percentage of Inventories the company currently has on hand to support the current amount of Revenue.
NVIDIA's Inventory-to-Revenue for the quarter that ended in Jan. 2024 was 0.23.
NVIDIA Total Inventories Historical Data
The historical data trend for NVIDIA's Total Inventories 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
Jan16
Jan17
Jan18
Jan19
Jan20
Jan21
Jan22
Jan23
Jan24
Total Inventories
979.00
1,826.00
2,605.00
5,159.00
5,282.00
NVIDIA Quarterly Data
Apr19
Jul19
Oct19
Jan20
Apr20
Jul20
Oct20
Jan21
Apr21
Jul21
Oct21
Jan22
Apr22
Jul22
Oct22
Jan23
Apr23
Jul23
Oct23
Jan24
Total Inventories
5,159.00
4,611.00
4,319.00
4,779.00
5,282.00
NVIDIA Total Inventories Calculation
Total Inventories includes the raw materials, work-in-process goods and completely finished goods of a company. It is a portion of a company's current assets.
NVIDIA (NAS:NVDA) Total Inventories Explanation
Inventory control is an important part of business operation. If a company does not have enough inventory, it may not be able to meet customers' required delivery time. If it has too much inventory, the cost of holding the inventory can be high.
1. In Ben Graham's calculation of Net-Net Working Capital (NNWC), inventory is only considered worth half of its book value.
NVIDIA's Net-Net Working Capital Per Share for the quarter that ended in Jan. 2024 is
4. Inventory-to-Revenue determines the ability of a company to manage their inventory levels. It measures the percentage of Inventories the company currently has on hand to support the current amount of Revenue.
NVIDIA's Inventory to Revenue for the quarter that ended in Jan. 2024 is calculated as
* 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.
Be Aware
Manufacturers with durable competitive advantages have the advantage that the products they sell do not change, and therefore will never become obsolete. Buffett likes this advantage.
When identifying manufacturers with durable competitive advantage, look for inventory and net earnings that rise correspondingly. This indicates that the company is finding profitable ways to increase sales which called for an increase in inventory.
Manufacturers with inventories that spike up and down are indicative of competitive industries subject to boom and bust.
NVIDIA Total Inventories Related Terms
Thank you for viewing the detailed overview of NVIDIA's Total Inventories provided by GuruFocus.com. Please click on the following links to see related term pages.
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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