This year, many flagship smartphones feature chipsets built on the impressive 3nm process, including the Apple A18 Pro and Qualcomm Snapdragon 8 Elite. As technology progresses, TSMC is set to begin manufacturing chips using a groundbreaking 1.4nm process by 2028.

The 1.4nm chips are expected to significantly enhance the capabilities of on-board artificial intelligence (AI). TSMC emphasizes that the power of these upcoming chips will allow devices to process AI requests directly on the device, eliminating the need to rely on remote servers.

This advancement not only boosts efficiency but also enhances user privacy by keeping data processing localized. In TSMC’s own words, their new A14 process is a major step forward, promising faster computing and better power efficiency to facilitate AI transformations in smartphones, making them smarter and more capable.

While TSMC has not disclosed specific partnerships for its 1.4nm process, it is highly likely that Apple will be among the first adopters, continuing its trend of utilizing TSMC’s latest technologies for its iPhone, iPad, and Mac products. Additionally, there are rumors that all 18 models of Apple’s 2026 iPhones will utilize TSMC’s upcoming 2nm chips, establishing Apple as a front-runner in chip adoption.

Understanding chip processes is vital—you often hear about “process” sizes in the industry. Simply put, a smaller process allows for more densely packed transistors, which reduces the time and distance electrical signals must travel.

This results in chips that are faster and more efficient, optimizing performance while being kinder to battery life. However, older processes like 6nm or 7nm still have their place, particularly for products that do not require cutting-edge technology and can benefit from reduced costs, making them suitable for mid-range and budget devices.

TSMC’s advancements solidify its lead over rival Samsung, which had initially announced plans for 2nm chips but has faced challenges with yield rates, allowing TSMC to establish its dominance in the chip manufacturing landscape.