Intel Total Non-Cash Items 2012-2026 | INTC
Intel annual/quarterly total non-cash items history and growth rate from 2012 to 2026. Total non-cash items can be defined as the total of all non-cash charges adjusting Net Income on the Cash Flows Statement
- Intel total non-cash items for the quarter ending March 31, 2026 were $11.418B, a 56.78% decline year-over-year.
- Intel total non-cash items for the twelve months ending March 31, 2026 were $29.778B, a 49.91% decline year-over-year.
- Intel annual total non-cash items for 2025 were $11.418B, a 56.78% decline from 2024.
- Intel annual total non-cash items for 2024 were $26.418B, a 154.88% increase from 2023.
- Intel annual total non-cash items for 2023 were $10.365B, a 46.46% increase from 2022.
|
Intel Annual Total Non-Cash Items (Millions of US $) |
|
|---|---|
| 2025 | $11,418 |
| 2024 | $26,418 |
| 2023 | $10,365 |
| 2022 | $7,077 |
| 2021 | $14,996 |
| 2020 | $12,504 |
| 2019 | $12,032 |
| 2018 | $10,289 |
| 2017 | $6,517 |
| 2016 | $9,059 |
| 2015 | $8,837 |
| 2014 | $8,813 |
| 2013 | $8,016 |
| 2012 | $8,099 |
| 2011 | $7,594 |
| Sector | Industry | Market Cap | Revenue |
|---|---|---|---|
| Computer and Technology | Semiconductor - General | $311.588B | $52.853B |
| Intel Corporation, one of the world's largest semiconductor company and primary supplier of microprocessors and chipsets, is gradually moving into data-centric businesses such as AI and autonomous driving. Intel is a dominant player for microprocessors in both consumer and enterprise markets. Data Center Group, Internet of Things Group, Mobileye, Non-Volatile memory solutions group and Programmable solutions Group and All Other business units form the crux of Intel's data-centric business model. DCG segment deals with servers, workstations and other products for cloud, enterprise, and communication infrastructure market. IOTG offers high-performance compute solutions and embedded applications. PSG segment offers programmable semiconductors, primarily FPGAs and structured ASICs. Mobileye is engaged in developing computer vision and machine learning-based sensing, data analysis, localization, mapping, and driving policy technology for ADAS and autonomous driving. | |||
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