Augmented Reality: Qualcomm introduces new processor for smaller AR glasses

With the Snapdragon AR2 Gen 1, Qualcomm has introduced a new processor specifically for augmented reality glasses. It is based on a multi-chip design and differs in one important respect from Qualcomm’s previous processors for augmented and virtual reality glasses. Because instead of combining all or at least as many components as possible on one chip, there are now three spatially separated. According to Qualcomm, this offers advantages, especially in terms of the design of the glasses.



The new multi-chip design should primarily enable more compact AR glasses due to the lower space requirement.

(Image: Qualcomm)

The fittings on the augmented reality glasses (AR glasses) must no longer make room for a large chip, but only a smaller one. The path can also be narrower, as the wiring of the individual components takes up less space due to the multi-chip design and the distributed tasks. Compared to the Snapdragon XR2, which is part of the Meta Quest 2 VR glasses, Qualcomm talks about a 40 percent smaller chip area and 45 percent fewer cable connections.

In detail, the Snapdragon AR2 Gen 1 consists of three chips. The AR processor is responsible for all operations related to perception and integrated displays. Therefore, it has its own CPU cores, an image processor (Spectra ISP), a graphics unit and an AI processor (Hexagon). The AR processor is placed – at least according to Qualcomm’s design proposal – in the real glasses.

The AR co-processor, on the other hand, sits in the bridge of the glasses above the nose. The sensors and cameras are connected via it. In addition, it has AI and computer vision capabilities to evaluate sensor and camera data. Dedicated CPU cores and an AI accelerator are also available here.



Qualcomm distributes the individual components of the Snapdragon AR2 Gen 1 to the temples and bridge of the AR glasses. The connection to the host is via WLAN.

(Image: Qualcomm)

The third chip sits in the left bracket and is responsible for the connections to the host device. The main component is the FastConnect 7800 communication platform with Wi-Fi 7, which is also used in the Snapdragon 8 Gen 2.



Two of the three components of the Snapdragon AR2 Gen 1: the AR processor on top, the AR co-processor on the bottom.

Qualcomm does not provide details about the CPU and graphics unit. When asked, the company only confirmed that it was not a “smartphone CPU”. The low computing power required and the goal of less than 1 watt of energy consumption stand in contrast to this.

A host is required as the Snapdragon AR2 Gen 1 does not have the power to do all the calculations on its own. According to Qualcomm, the host does not necessarily have to be a smartphone, and the company also named PCs as suitable devices. It is crucial that the manufacturer of the AR glasses offers a companion app for the respective platform – such as Android, iOS or Windows. Ideally, the host can handle Wi-Fi 7 due to the high bandwidth and low latency, but the standard is not a must. In the conversation, Qualcomm called Wi-Fi 6E sufficient for smooth data exchange, but Wi-Fi should also offer enough bandwidth and sufficiently low latency.

Compared to the Snapdragon XR2 previously offered for AR glasses, Qualcomm is talking about a 50 percent reduction in energy consumption. At the same time, AI performance is said to have increased by up to 150 percent in some cases. This applies above all to image processing, including object recognition and tracking of hand movements.

The first AR glasses based on Snapdragon AR2 Gen 1 manufactured in 4 nanometers are already being developed by Lenovo, Oppo, Xiaomi and some other manufacturers. However, Qualcomm does not expect availability until the second half of 2023. Software developers can adapt their programs to Snapdragon AR2 Gen 1 via an SDK. The collaboration with, among others, Adobe and Niantic aims to simplify the creation of content. Adobe relies on a link to its own programs to deploy content without programming knowledge.


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