Anduril, Qualcomm partner on new line of US-made laptops

Anduril and Qualcomm Launch US-Made Rugged Laptops for Military & Government

By Stephen Nellis

Anduril and Qualcomm’s Strategic Move in Defense Technology

Overview of the Partnership

SAN FRANCISCO, Oct 27 (Reuters) - Defense tech firm Anduril said on Tuesday it plans to build a series of rugged computers in the United States for government and military customers, using chips from Qualcomm.

Anduril’s Growth and Market Position

Anduril, led by founder Palmer Luckey, has been announcing new military weapons and drones at a rapid pace and is in talks to raise funding at a valuation of about $100 billion. The company reported $2.2 billion in revenue in ⁠2025 ​and doubled its workforce, it said in January.

Production and Supply Chain Details

US-Based Manufacturing

The BlueChip laptops will be made in the US, with circuit board assembly planned for an Anduril plant in Ohio. Anduril said it is also developing US production for the laptop's case, batteries and other key parts while qualifying other US suppliers for production.

Phased Approach to Supply Chain

In a press announcement, the companies said on Tuesday they plan to take a "phased approach" aimed at "establishing an end-to-end American supply chain."

Qualcomm’s Role and Technological Advancements

Snapdragon X Chips and Manufacturing

During a press conference, Qualcomm CEO Cristiano Amon said that the Snapdragon X chips for the laptops will be made by Taiwan Semiconductor Manufacturing Co at its Arizona facilities.

Security and AI Features

Qualcomm is a relatively new entrant to the laptop chip market and has been adding security and AI features to its chips. During the press conference, Anduril's Luckey said that handling AI work privately on a laptop is an important feature for government and defense customers.

Onboard AI Inference for Sensitive Data

"I've been using my BlueChip laptop to do a whole bunch of local model work where I don't I don't want to, and actually am not allowed to, send certain information out into the cloud," Luckey said. "Having devices that can do a really good job of onboard AI inference, running local models, is actually really, really important.”

(Reporting by Stephen Nellis in San Francisco; editing by David Gaffen)