Smartglasses are increasingly being used to capture photos and videos, but how well do their cameras perform in real-world situations?
Over the past few years, those devices have evolved from simple companion products into increasingly capable imaging tools. Many of today’s smartglasses integrate cameras that allow users to capture hands-free moments, whether during everyday activities, travel, or social interactions. As these devices become more popular, understanding the quality of the images they produce becomes increasingly important.
To better understand the current state of smartglasses imaging, we recently evaluated seven models currently available on the market:
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- Rayneo X3 Pro
- Ray-Ban Meta Display
- Ray-Ban Meta Gen2
- INMO Air 3
- HTC Vive Eagle
- Rokid AI
- Quark AI S1
Using a dedicated imaging benchmark built upon DXOMARK’s established evaluation methodology, our experts assessed the image quality of these smartglasses across a wide range of conditions, from bright outdoor environments to challenging indoor and low-light scenes. The objective was not only to identify the strengths of current smartglasses cameras but also to better understand the situations where smartglasses imaging systems still face limitations and where further innovation and progress are needed.
To establish a meaningful reference point and to better assess the maturity of smartglasses imaging, we selected the front camera of the Apple iPhone 13 as a reference device. Its camera specifications are representative of those currently found in most smartglasses, enabling a fair comparison between two devices with similar hardware capabilities. Although introduced nearly five years ago, the iPhone 13 remains a highly relevant reference, providing valuable context for evaluating how current smartglasses compare with a previous-generation smartphone camera.
How Smartglasses Cameras Were Evaluated
Building on DXOMARK’s established evaluation methodology, the benchmark combines objective laboratory measurements with perceptual analysis of images and videos captured in real-world scenarios. This comprehensive approach allows us to evaluate not only quantifiable image quality metrics, but also the overall visual experience delivered to end users.
The benchmark encompasses a broad range of photo and video use cases, covering representative everyday scenarios under various lighting conditions, including outdoor daylight, indoor environments, low light, and high-contrast scenes.
These scenarios were selected to reflect the environments and lighting conditions users encounter most frequently in everyday life. While capturing an image on a sunny day may appear straightforward, smartglasses cameras must also perform reliably as users move through rapidly changing environments, such as transitioning from outdoors to indoors, walking at sunset, or facing scenes with both bright highlights and deep shadows.
To fully characterize their capabilities, the benchmark also includes challenging situations that push imaging systems beyond typical operating conditions. Unlike smartphones, which are intentionally raised to capture a scene, smartglasses are continuously worn and record the world from the user’s perspective. As a result, even natural head movements or small changes in orientation can introduce complex imaging challenges, including exposure variations, motion blur, stabilization issues, and rapidly changing scene composition.
By combining representative everyday scenarios with more demanding test conditions, the benchmark provides a comprehensive assessment of real-world camera performance while highlighting the situations where current smartglasses still have the greatest room for improvement.
Outdoor Performance Shows Promising Progress
In non-challenging lighting conditions, smartglasses demonstrate their best performance. Some models surpassed the performance delivered by the iPhone 13 Selfie camera, especially in terms of contrast and dynamic range
These results suggest that manufacturers have made significant progress in optimizing image processing pipelines for bright daylight conditions, where sufficient light allows cameras to operate closer to their full potential.
The ability to capture usable images in outdoor environments is particularly important for smartglasses because many of their most common use cases occur outdoors. Whether documenting a walk, recording a first-person perspective, or capturing spontaneous moments without reaching for a smartphone, users are likely to rely on these devices in well-lit environments.
iPhone 13 (Selfie camera)
However, image quality was not always consistent. Differences in color rendering, skin tone reproduction, and contrast management remained visible across devices. While some smartglasses delivered natural-looking results, others struggled to reproduce colors accurately or maintain a balanced rendering across different scenes. This variation highlights the importance of software tuning and image processing in determining overall image quality.
Ray-Ban Meta Display (1000Lux – 6500K)
iPhone 13 Selfie camera (1000Lux – 6500K)
Rokid AI Glasses (1000Lux – 6500K)
Indoor Photography Reveals Current Limitations
When moving indoors, performance became more variable. Many smartglasses struggled to maintain the same level of detail and exposure consistency observed in outdoor conditions. Image noise became more noticeable, and differences between devices increased. In some cases, images appeared softer, while others showed visible fluctuations in exposure or color rendering depending on the scene. In this scenario, the iPhone 13 front camera consistently outperformed the smartglasses.
Indoor environments often present more complex lighting situations than outdoor scenes. Artificial light sources, mixed color temperatures, and lower overall brightness levels place additional demands on camera systems. These conditions quickly reveal the limitations of sensors, optics, and image processing algorithms.
iPhone 13 (Selfie camera)
At DXOMARK, we expected such challenges. Smartglasses must integrate cameras into a compact form factor, which limits the size of sensors and optical components available to manufacturers. Compared with smartphones, smartglasses have less physical space available for imaging hardware, making it more difficult to maintain image quality as lighting conditions become less favorable.
Low-Light Conditions Remain the Biggest Challenge
Low-light scenes proved to be the most demanding scenario for smartglasses cameras.
Across most tested devices, image quality declined as lighting levels decreased. Detail preservation became more difficult, noise sometimes considerably increased, and exposure was often less stable. As a result, images captured in darker environments generally appeared less detailed and less consistent than those captured in brighter conditions.
Low-light performance remains one of the most difficult challenges in digital imaging. When less light reaches the sensor, cameras must rely more heavily on image processing to compensate, often leading to compromises between detail retention, noise reduction, and overall image appearance.
iPhone 13 (Selfie camera)
Compared with the smartglasses tested, the iPhone 13 front camera maintained stronger overall performance in these situations, producing cleaner images with more consistent exposure and better detail retention. This reflects the advantage that smartphones continue to hold thanks to years of development in sensor technology, optics, and computational photography.
HTC Vive Eagle (10Lux – 2700K)
Ray-Ban Meta (10Lux – 2700K)
iPhone 13 Selfie camera (10Lux – 2700K)
What the Benchmark Tells Us About Smartglasses
Our benchmark highlights the remarkable progress smartglasses have made in a relatively short time. Current-generation devices already deliver a solid imaging experience in favorable lighting conditions, particularly outdoors, where several models approach the image quality of previous-generation smartphones.
However, the benchmark also shows that important gaps remain before smartglasses can compete with today’s flagship smartphones. Even in bright outdoor conditions, some devices still struggle with high-contrast scenes, color and skin tone rendering, and overall image tuning. These limitations become even more apparent indoors and in low light, where the constraints of current sensors, optics, and image processing pipelines lead to visible degradations in exposure, detail preservation, and noise management. In addition, the first-person nature of smartglasses introduces unique challenges in exposure adaptation, stabilization, and image consistency as users move through dynamic environments.
For consumers, smartglasses are already emerging as compelling devices for hands-free content capture and AI-assisted everyday experiences. While smartphones remain the benchmark for delivering consistently high image quality across all shooting conditions, the gap is narrowing as smartglasses imaging technology continues to evolve.
Looking ahead, advances in sensor technology, optics, computational photography, and on-device AI will be key to further improving image quality and user experience. As the category matures, objective benchmarking will become increasingly important, not only to measure technological progress, but also to identify the innovations that will enable smartglasses to become a credible imaging platform for everyday use.
