Low-Light Performance

The Galaxy S26 Ultra brings a few hardware updates, including a wider aperture on the main camera and a new 5× telephoto lens. These changes help the camera capture more light, which improves performance in difficult conditions such as low-light photography and video.

Together with Samsung’s Pro Scaler technology, the phone shows better noise control and a more balanced level of detail compared with the Galaxy S25 Ultra. Images taken in low light look cleaner overall, especially when slightly zooming in on the main camera.

Despite these improvements, the S26 Ultra still trails the iPhone 17 Pro in challenging low-light scenes. In our comparisons, Samsung’s device showed more visible luminance noise and slightly less detail in portraits captured in dim environments.

Samsung Galaxy S26 Ultra

Apple iPhone 17 Pro

Portrait Photography: Building on the Previous Generation

Portrait performance has improved compared with the Galaxy S25 Ultra. The previous model often struggled with color accuracy in difficult lighting, sometimes producing unnatural skin tones. With the S26 Ultra, Samsung appears to have addressed this issue. Face brightness is also fairly similar between Samsung and Apple devices. In some lower-contrast scenes, the S26 Ultra even applies a slightly stronger brightness boost to faces, which may help portraits appear more flattering.

Samsung Galaxy S26 Ultra

Samsung Galaxy S25 Ultra

Areas for Improvement

Even with these improvements, the S26 Ultra still faces some challenges in portrait photography. Our tests revealed occasional autofocus inconsistencies, particularly in low light or complex lighting situations. When focus is slightly off, facial details can appear softer and exposure on the face may be less accurate.

Portrait mode (bokeh) is another area where the phone still struggles to match the best devices in the segment. Images sometimes show lower clarity and less effective noise reduction compared with competing flagship phones. Subject separation can also be inconsistent. In some scenes, small segmentation errors appear around the edges of the subject, creating visible gaps between the person and the blurred background.

Samsung Galaxy S26 Ultra vs iPhone 17 Pro Comparison

(Left: Samsung Galaxy S26 Ultra - Right: Apple iPhone 17 Pro) - Beyond portrait quality, there is also a noticeable gap in segmentation accuracy, with flagship devices overall failing to deliver consistently satisfying results in this mode.

Lack of image clarity and noise reduction with noticeable gap in subject segmentation on the S26 Ultra

Zoom Remains a Key Strength

One area where the Galaxy S26 Ultra continues to perform very well is zoom. Thanks to its dual telephoto system, the phone delivers strong results across many zoom levels in both photo and video.

In many situations, the S26 Ultra still preserves slightly more detail than the iPhone 17 Pro. However, competitors are quickly closing the gap. Motorola’s Signature flagship, for example, performs particularly well in medium-range telephoto portraits around 3× zoom, where it preserves more facial texture and detail than the Samsung device.

Samsung Galaxy S26 Ultra

Motorola Signature

Initial Assessment

In this quick review comparing its performance with other major flagship smartphones, we’ve seen that the Samsung Galaxy S26 Ultra brings noticeable improvements over the previous generation, particularly in low-light capture, noise control, and skin-tone rendering. These refinements make it a more capable device for portrait photography, although some limitations remain. Competing flagship smartphones still deliver cleaner low-light portraits, more consistent subject separation, and stronger detail in certain zoom scenarios.

Overall, the Galaxy S26 Ultra remains a strong contender especially for zoom photography but it now faces increasingly strong competition in portrait and low-light imaging within the ultra-premium segment.

A full evaluation, including detailed scores and a complete analysis of the camera performance, will be published soon so stay tuned for the full review.

The post Samsung Galaxy S26 Ultra: Comparing Performance in the Ultra-Premium Class appeared first on DXOMARK.

Since 2023, DXOMARK has been conducting Insights studies worldwide to better understand consumer preferences in portrait photography. Going beyond traditional performance metrics, these studies focus on how users actually perceive images: what satisfies them, what frustrates them, and what they truly expect from smartphone cameras, while also identifying the underlying technical challenges faced by the industry.

Built on a unique methodology, DXOMARK Insights combines expert analysis with structured feedback from real users. This approach enables a deep understanding of portrait rendering preferences across different user profiles, skin tones and shooting conditions.

After conducting studies in Europe, China, and India, DXOMARK has now expanded its research into a new geographic area: the Middle East. Riyadh was selected as the study location due to its position at the crossroads of continents and cultures, offering a broad diversity of skin tones. This made it an ideal environment for exploring inclusive portrait performance under a wide range of real-world conditions.

The framework of the Study

The DXOMARK Insights study was conducted in Riyadh, with a panel of 75 participants aged 18 to 45, representing a wide range of user profiles.

The evaluation covered:

• • 90 portrait scenes, spanning outdoor, indoor, and low-light conditions
  • A broad diversity of skin tones, including fair, medium, and dark
  • Realistic use cases designed to reflect everyday photography scenarios

The study took a unique approach to previous studies by exploring the performance of mid-range priced smartphones, including a higher price device as well as a reference.

The devices that were included in this study were:

• • Google Pixel 9a
  • Tecno Camon 50 Ultra 5G
  • Samsung Galaxy A56
  • Apple iPhone 17 Pro

Key findings at a glance

According to Riyadh consumers, here are the 3 main takeaways from this study:

• • Google Pixel 9a and Tecno Camon 50 Ultra 5G emerged as the most compelling devices for portrait overall, largely due to their ability to deliver natural skin tone renderings for a wide range of skin types
  • Indoor and low-light portraits remain challenging use cases for most devices, particularly rendering darker skin tones, yet some devices demonstrate clear advantages in these conditions
  • Face brightness is a critical drive of user satisfaction but balance is key: images that are too bright or too dark are consistently rejected.

Overall preferences and device ranking

According to Middle Eastern consumers, the Google Pixel 9a is the most preferred device overall across all scenarios. It delivered generally bright images with well-balanced contrast and neutral white balance. Because it is the most balanced device, with consistent rendering across conditions and very few failure cases, the Google Pixel 9a ends up as the preferred device in this comparison.

In terms of colors, it provides neutral rendering that often outperforms the warm rendering of the iPhone 17 Pro from a user’s perspective. In addition to that, it did a very good job at rendering bright faces while preserving balanced contrast which is perceived as more pleasing than the weaker boost visible on the iPhone 17 Pro and the excess of brightness and contrast boost on the Tecno Camon 50 Ultra 5G. The Tecno Camon 50 Ultra 5G ranked second globally but stood out in specific conditions.

It delivered bright images with a globally neutral white balance and a natural skin tone rendering. It also stood out in specific conditions. Notably, in indoor portrait scenes, the Tecno Camon 50 Ultra 5G was the most preferred device, outperforming all others. However, the high brightness along with a strong global contrast sometimes led to rejection from some users.

The Samsung Galaxy A56 was the least preferred from the panel across lighting conditions. Lacking HDR support, it was perceived as producing significantly darker renderings compared to the other devices, resulting in lower overall preference.

The Apple iPhone 17 Pro, included as a reference device to compare the performance with the mid-range devices, was sometimes rated as delivering insufficient face brightness, despite maintaining a balanced contrast. In complex indoor environments, it was also perceived as producing a warmer color cast and warmer skin tones.

Tecno Camon 50 Ultra 5G

Samsung Galaxy A56

Google Pixel 9a

Tecno Camon 50 Ultra 5G

Apple iPhone 17 Pro

Google Pixel 9a

Tecno Camon 50 Ultra 5G

Apple iPhone 17 Pro

Google Pixel 9a

Tecno Camon 50 Ultra 5G

Samsung Galaxy A56

Google Pixel 9a

Satisfactions related to these scenes

Indoor and low-light portraits: still the biggest challenge

Indoor and low-light scenarios continue to be among the most difficult environments for portrait photography. As we can observe from the overall results of the study, the overall satisfaction index is the lowest under these lighting conditions.

Due to two main factors:

First, the scenes are characterized by low illumination levels and limited light diffusion, placing strong constraints on facial brightness rendering, contrast management, and mid-tone tone mapping. Under these conditions, several devices exhibit underexposure, particularly affecting facial regions. Our insights show that face brightness needs to be high enough or the impact where accurate luminance reproduction is critical for perceived quality.

Reason for rejection per device

Second, the lighting environments are complex, involving multiple light sources that create mixed illumination conditions. This complexity increases the difficulty of achieving consistent color rendering and tonal balance. As a result, some devices produce renderings that appear excessively warm, contributing to lower global user satisfaction preferences.

Tecno Camon 50 Ultra 5G

Google Pixel 9a

Apple iPhone 17 Pro

In this specific context, for Indoor scenes, we observe that the Tecno Camon 50 Ultra 5G stood out, being the most preferred device from the consumer surveyed. In this study, it was preferred 63% of the time in indoor conditions, making it the preferred device among the tested ones.

Consumers highlighted its ability to deliver vivid yet faithful colors, while preserving luminous skin tones in complex indoor lighting, an area where many competing devices still struggle.

In lowlight, user ‘s are still used to higher image degradation, and it might affect their expectations. Overall devices show high variations of rendering between smartphones model and some failures with exposure strategy. With all the challenges of exposure, noise reduction, etc related to low light photography, smartphones are forced to do some trade-offs that limit the capacity to produce natural and saturated colors and skin rendering. A wide margin for improvements remains to shoot natural and pleasant portraits in low light conditions.

Tecno Camon 50 Ultra 5G

Samsung Galaxy A56

Google Pixel 9a

Satisfaction related to this scene

Rejection on all devices for this specific scene

The impact of brightness and contrast on user perception & preferences

Brightness level is one of the strongest drivers of user preference. Consumers consistently favored images that were neither too bright nor too dark, emphasizing the importance of balance.

Reason for rejection per device

This was particularly visible for the Samsung Galaxy A56, which suffered from a high number of rejections due to too low brightness on the face. For the iPhone 17 Pro, the most frequent rejection reason was that faces were sometimes appearing too dark.

On the other hand, in some cases, when the Tecno Camon 50 Ultra 5G device delivered a too high brightness, it was one of the top rejection reasons.

Tecno Camon 50 Ultra 5G

Google Pixel 9a

Apple iPhone 17 Pro

Picture Ligthness vs Subject Lightness per smartphone for scene above (SDR) 

(Blue : Tecno Camon 50 Ultra – Yellow : Apple iPhone 17 Pro – Green : Google Pixel 9a)

Satisfaction related to this scene

Reason for rejection per device

When the face and background are too bright, the result can be a loss of information and visible clipped area on face. This is even more impacting when it is related to strong global contrast of images and that bright part are facing deep shadowed area.  details and overall contrast perception. The bright areas can be too bright in some examples leading to some slight clipping on the face.

Tecno Camon 50 Ultra 5G

Google Pixel 9a

Samsung Galaxy A56

Picture Lightness per device for scene above (HDR)

Reason for rejection per device

Conclusion

This DXOMARK Insights study highlights the importance of portrait rendering, balanced brightness, and robust performance in challenging lighting conditions. It also reinforces the value of consumer-centric evaluation methods in understanding not just how cameras perform but how they are truly perceived.

As smartphone imaging continues to evolve, aligning technical choices with real user expectations will remain a key differentiator for manufacturers aiming to deliver meaningful and satisfying photography experiences

The post Understanding portrait preferences: DXOMARK Insights in Riyadh appeared first on DXOMARK.

Based on the findings of the DXOMARK Global Insights 2025 research project conducted across Paris, Shanghai, and Jeddah, DXOMARK convened an official roundtable with members of the DXOMARK Imaging Expert Committee. Together with DXOMARK image engineers, the experts explored core topics such as user preferences, skin tone rendering, and real-world usage scenarios, offering critical analysis of today’s consumer expectations.

The roundtable brought together imaging professionals from across the industry: 

• • Cem Kıvırcık – Senior Imaging Journalist and Photographer
  • Marko Risovic – Documentary Photographer
  • Renaud Labracherie – Senior Photojournalist
  • Juanmao Tong – Senior Professional in Mobile Photography
  • Gugugu – Digital Technology Content Creator
  • Madder – Editor-in-Chief, Content Department, iRentals
  • Hervé Macudzinski – Director of Image Science, DXOMARK
  • Coraline Hillairet – Senior Image Engineer, DXOMARK

The Committee brings together global imaging experts, academic institutions, and industry partners through open collaboration and content co-creation, driving the development of next-generation imaging test standards and advancing the industry as a whole. Learn more about the Expert Committee

DXOMARK Global Insights 2025 – Is Imaging really “too many tastes to satisfy”

Research methodology

In addition to applying our typical Insights methodology (Learn more), for this specific study, a cross validation was conducted: images were captured across three regions and independently annotated by user groups from each location. This methodology enabled DXOMARK to compare regional preferences and assess whether a unified image quality tuning strategy could satisfy users worldwide.

The study included flagships from major brands (vivo, Samsung, Huawei, Oppo, Xiaomi), one mid-range smartphone per region and a professional camera rendering

(Note that this study was conducted end of summer 2025, before the release of the most recent flagships).

Research findings

Research suggests that a single camera tuning scheme can satisfy consumers across different regions. In particular, the portrait performance of the vivo X200 series was widely appreciated by users in all three regions, demonstrating its ability to align with diverse aesthetic preferences.

Across all tested devices, the vivo series consistently ranked among the top performers in consumer evaluations across all three regions. Oppo Find X8 Ultra and Huawei Pura 80 Ultra secured second and third place respectively.

SI = Satisfaction Index [Blue background refers to the Paris panel, while the Orange background refers to the Shanghai panel] 

The DXOMARK Satisfaction Index is a numerical representation of user preferences. It is a combination of two distinct aspects that we measured in this study: One measures preference and the other measures rejection. By combining these two results, we were able to gather insights not only about user preferences but to quantify them as well.

In cross-evaluations between Shanghai and Paris, users in both locations showed a clear preference for portraits captured by vivo smartphones and photographer rendering, citing higher brightness and more pleasing skin tones.

SI = Satisfaction Index [Blue background refers to the Paris panel, while the Orange background refers to the Shanghai panel] 

For this example, both groups ranked vivo X200s and OPPO Find X8 Ultra among the top three for imaging quality. The Samsung Galaxy S25 Ultra was excluded due to unnatural skin tones in low-light conditions.

If You Love It, Will Others Feel the Same?

DXOMARK Insights

While a unified tuning approach is broadly feasible, regional and individual differences remain significant. In some cases, users in China and France expressed completely opposite preferences when evaluating the same images.

Research Findings

SI = Satisfaction Index [Blue background refers to the Paris panel, while the Orange background refers to the Shanghai panel] 

In the Shanghai study, the results highlighted regional differences in preferred rendering styles. Shanghai users showed a strong preference for the vivo X200S and photographer rendering, while Paris users favored vivo’s rendering. Despite these differing preferences, both panels reported comparable satisfaction index, with only minor variations observed across the two regions.

SI = Satisfaction Index [Blue background refers to the Paris panel, while the Orange background refers to the Shanghai panel] 

In the indoor use case, user preferences showed partial overlap: Paris users favored warmer color rendering while Shanghai users preferred less warm more neutral color rendering.

Real-World Portrait Photography : What Truly Matters to Users?

DXOMARK Insights

Despite rapid advances in smartphone imaging, user evaluation criteria in real-world scenarios remain remarkably consistent.

Research Findings

Comparing Shanghai surveys from 2024 and 2025 revealed nearly identical rejection reasons: images that were too dark, unnatural skin tones, insufficient facial brightness, or lack of skin fairness.

It is noteworthy that the satisfaction index for vivo devices increased in 2025, driven by changes in rendering that delivered softer facial contrast, more controlled peak brightness and reduced facial shine.

Roundtable Open Discussion Among the Expert Committee Members

In addition to exploring the findings of our global Insights studies, we opened the discussion for a debate on various topics related to smartphone imaging and user preferences. Here are some thoughts from our experts on these topics.

Common Failure Modes in Skin Tone Rendering

• • Madder noted that strong backlighting can cause exposure flicker, while unsmooth zooming or camera switching in video often leads to white balance and sharpness issues that are especially noticeable to non-professional users.
  • Gugugu described skin tone as a “memory color,” stressing that cameras must reproduce how users remember colors, not just objective values. He recommended improving multispectral recognition to better handle complex lighting.
  • Marko Risovic pointed out that portrait prioritization can sometimes strip background environments of texture, urging manufacturers to better balance subject and surroundings.

Localization vs. Standardization

Cem Kıvırcık argued that while cultural expectations matter, manufacturers should always offer standard or natural modes:

“Excessive smoothing and brightening may satisfy some preferences, but they often undermine authenticity.”

The Role of Customization Tools

Customization tools were widely viewed as essential not to add filters, but to give users control over aggressive AI processing. As aesthetics evolve and self-expression becomes more important, such tools are expected to play an increasingly critical role in mobile imaging.

What Image Styles Do Users Want?

Experts agreed that users are increasingly drawn to authentic, true-to-life imagery. While vibrant, share-ready photos were once dominant, demand is growing for images that preserve natural textures especially in skin tones and environmental detail. Consistent color rendering across focal lengths and accurate reproduction of key colors remain top priorities.

Conclusion and Path Forward

This cross-regional research highlights strong common ground in consumer expectations, demonstrating that a unified camera tuning strategy can successfully address the needs of users across global markets. At the same time, regional preferences shaped by cultural context, aesthetic sensibilities, and individual taste continue to influence how imaging attributes are perceived.

Across all regions, accurate and pleasing face and skin-tone rendering consistently emerged as a universal priority, underscoring its central role in user satisfaction.

Building on these insights, DXOMARK will continue to convene regular roundtable discussions through the Imaging Experts Committee. Anchored in real consumer feedback, this global open-collaboration aims to meaningfully support the development of next-generation imaging evaluation standards and contribute to the ongoing evolution of the imaging industry.

The post Highlights from the DXOMARK Imaging Experts Committee Roundtable appeared first on DXOMARK.

Modern smartphones are increasingly capable of reaching exceptionally long focal lengths thanks to high-resolution sensors, hybrid optical systems, and advanced computational photography. However, as zoom ratios increase, software processing plays an even greater role, influencing how details, fine textures, and overall scene rendering are reproduced.

In this comparison, we examined long range telephoto performance across five top-tier devices: Apple iPhone 17 Pro, Honor Magic 8 Pro, OPPO Find X9 Pro, vivo X300 Pro, and Xiaomi 17 Pro Max. Our intention was to observe how each phone behaves when pushed toward the upper limits of zoom not only on static landscapes, but also on zoomed-in portraits where facial rendering becomes more challenging.

Portrait Performance

Apple iPhone 17 Pro

Apple iPhone 17 Pro (8x zoom)

Honor Magic 8 Pro

Honor Magic 8 Pro (10x zoom)

OPPO Find X9 Pro

OPPO Find X9 Pro (6x zoom)

vivo X300 Pro

vivo X300 Pro (10x zoom)

Xiaomi 17 Pro Max

Xiaomi 17 Pro Max (10x zoom)

Portraits under long-range zoom further amplified stylistic differences between devices. The iPhone 17 Pro rendered subjects slightly darker and warmer, producing a natural yet more subdued interpretation. The OPPO Find X9 Pro leaned toward a softer result with moderate detail, while Honor Magic 8 Pro produced bright, crisp faces with subtle signs of motion blur.

The Xiaomi 17 Pro Max delivered clearly defined facial detail, and vivo X300 Pro produced one of the brightest and sharpest portrayals overall. When viewed closely, vivo, Honor, and Xiaomi all displayed slight sharpening behavior that became noticeable on fine details, but in full-frame viewing, each device presented a balanced and visually pleasing portrait representation. These variations reflect each brand’s priority between natural rendering and enhanced clarity when operating at extreme zoom levels.

Cityscape Performance

Apple iPhone 17 Pro

Apple iPhone 17 Pro (8x zoom)

Honor Magic 8 Pro

Honor Magic 8 Pro (10x zoom)

OPPO Find X9 Pro

OPPO Find X9 Pro (6x zoom)

vivo X300 Pro

vivo X300 Pro (10x zoom)

Xiaomi 17 Pro Max

Xiaomi 17 Pro Max (10x zoom)

At extremely long zoom distances, all five smartphones captured usable and visually appealing landscape results, yet their processing styles showed clear differentiation. The iPhone 17 Pro delivered a natural overall rendering with a restrained approach to sharpening, while the OPPO Find X9 Pro maintained stable detail even at a slightly lower zoom level, though minor flare reduced contrast in certain situations.

The Honor Magic 8 Pro produced clean images but relied on heavier detail processing, resulting in occasional unnatural nuances when examined closely. Similarly, vivo X300 Pro delivered strong detail and brightness, though its processing introduced more noticeable artifacts in fine textures.

The Xiaomi 17 Pro Max followed a similar path, producing generally pleasant full-frame results, yet slight motion blur reduced clarity and contrast under deep magnification. Despite these variations, all devices performed competently, with differences becoming most apparent during zoom-in evaluation.

Conclusion

All five flagships demonstrated convincing capability at long zoom ranges, confirming how far mobile telephoto systems have evolved. The iPhone prioritizes a restrained and natural style, while OPPO focuses on stability and balance even with a slightly shorter zoom factor. Honor offers sharp and clean results, though sometimes with visible processing at close inspection, whereas vivo pushes clarity and brightness further for a crisp, high-impact rendering. Xiaomi sits closely beside vivo and Honor with a similarly detailed output, though fine-detail softness may appear in movement-heavy scenes.

In the end, each manufacturer approaches high-zoom photography with its own vision from natural rendering to clarity-driven enhancement allowing different user preferences to align with different devices.

The post Long range telephoto Zoom China’s Flagship Comparison: Cityscape and Portrait appeared first on DXOMARK.

Building on that foundation, this new installment focuses on night photography, an area where flagship smartphones increasingly differentiate themselves. We compared five major devices: Apple iPhone 17 Pro, HONOR Magic8 Pro, OPPO Find X9 Pro, vivo X300 Pro, and Xiaomi 17 Pro Max.
Our image quality team analyzed each photo to better understand how these models handle both night & low-light main camera shots and telephoto night scenes, two situations that challenge even the most advanced devices.

Low-Light Performance

In this nighttime scenario, the five smartphones demonstrated noticeably different approaches to rendering the scene and presenting the subject.

Apple iPhone 17 Pro

Honor Magic8 Pro

Oppo Find X9 Pro

vivo X300 Pro

Xiaomi 17 Pro Max

The Xiaomi 17 Pro Max produced a darker overall image while still keeping the subject’s face visibly well-defined. On the opposite end of the spectrum, HONOR Magic8 Pro and the iPhone 17 Pro delivered significantly brighter interpretations, giving the scene a more illuminated appearance.

Among the devices, Apple’s rendering tended to appear slightly cooler compared to the others, while OPPO introduced a warmer interpretation of the subject’s skin. These stylistic choices created subtle but noticeable differences in the overall mood of the images.

In terms of detail, the HONOR Magic8 Pro displayed a somewhat more processed look, giving the scene a style that may appeal to users who prefer a highly refined, digitally enhanced aesthetic. The iPhone 17 Pro showed a bit more visible grain across the frame due to its imaging mode choice, though its overall luminance remained balanced.
It’s worth noting that for this scene, the iPhone automatically switched to a 12MP mode designed for improved night performance rather than the higher resolution it used in other tests.

Low-Light Telephoto Comparison

The telephoto evaluation highlighted the differences in each device’s optical setup:

• • Xiaomi: 115 mm (5×)
  • vivo: 85 mm (3.5×)
  • OPPO: 70 mm (3×)
  • HONOR: 85 mm (3.7×)
  • Apple: 100 mm (4×)

Honor Magic8 Pro

Apple iPhone 17 Pro

Oppo Find X9 Pro

vivo X300 Pro

Xiaomi 17 Pro Max

Each device produced a well-rendered telephoto image, though their visual interpretations varied. HONOR and Xiaomi offered the brightest overall results, while OPPO and vivo delivered a slightly more subdued rendering of the scene.

Color presentation remained pleasant across all models, with Apple leaning slightly warmer and Xiaomi closer to a neutral balance. These differences shaped the atmosphere of each image rather than significantly altering accuracy.

In terms of clarity, vivo and HONOR produced the sharpest and most defined telephoto results in this night scene. OPPO’s output appeared softer in comparison, while Xiaomi introduced a small trace of motion softness, likely due to longer capture processing. The iPhone 17 Pro showed more visible grain, which gave its telephoto image a more textured appearance than the others.

A JOD (Just Observable Difference) is the smallest change in quality that the human eye can detect. On this scale, a gap of 1 JOD means a noticeable improvement therefore the higher JOD values corresponds to better performance in texture / noise.

Conclusion

Each flagship smartphone delivered capable night photography results, yet the differences remain significant enough to influence user preference. Xiaomi and Honor favored brighter interpretations, vivo provided some of the clearest telephoto detail, OPPO leaned toward a softer aesthetic, and Apple maintained its characteristic rendering style with a balance between brightness and softness. These variations reflect the unique imaging philosophies of each manufacturer, allowing users to choose the device that aligns best with their visual preferences and typical nighttime shooting habits.

We will continue to dive into the performance of these newly released flagships by testing these in additional real world scenarios. Stay tuned!

The post Low-Light & Night Camera Performance : A Closer Look at China’s Latest Flagship appeared first on DXOMARK.

In this first episode, we focused on two common scenarios that reveal a device’s photographic strengths and processing decisions: a daytime portrait and a backlit portrait. These scenes were selected because they represent situations encountered by most smartphone users, whether capturing a quick portrait outdoors or photographing a subject with strong light behind them.

Daytime Portrait Performance

Daylight portraits offer a relatively controlled setting, yet they also allow key differences in image processing to emerge. In this scenario, all five devices produced solid results, though each approached subject rendering and scene interpretation in its own way.

Xiaomi 17 Pro Max

Honor Magic8 Pro

Apple iPhone 17 Pro

Oppo Find X9 Pro

vivo X300 Pro

The Xiaomi 17 Pro Max, vivo X300 Pro, and OPPO Find X9 Pro delivered portraits with clear and natural-looking subject representation, maintaining consistent facial rendering and a generally realistic overall appearance. These three devices also remained relatively close in terms of color interpretation, showing only slight variations from one another.

The HONOR Magic8 Pro produced a more processed and stylized look, which may appeal to users who prefer a more enhanced aesthetic. Its rendering also appeared noticeably cooler than the other models, contributing to a less natural impression.

The Apple iPhone 17 Pro offered the warmest interpretation of the scene, with a softer and more subdued representation of the subject compared with the other devices.

Despite these differences, all smartphones handled the daylight portrait scenario effectively, with variations largely reflecting each manufacturer’s preferred interpretation of color, facial detail, and overall portrait style.

Backlit Scene Performance

The backlit test created a more demanding environment, pushing each device to balance the bright background with the subject positioned in front of it. This scenario accentuated the distinctions between the devices far more than the daylight portrait.

vivo X300 Pro

Oppo Find X9 Pro

Apple iPhone 17 Pro

Honor Magic8 Pro

Xiaomi 17 Pro Max

The Xiaomi 17 Pro Max delivered the brightest representation of the subject, making the face more prominent in the frame. In contrast, the iPhone 17 Pro rendered the subject noticeably darker, resulting in a more shadowed appearance.

The vivo X300 Pro and OPPO Find X9 Pro preserved more information in the sky and background areas, offering a better balance between the subject and the environment. Their handling allowed for greater visibility of bright elements behind the subject.

Flare significantly affected both the iPhone 17 Pro and the OPPO Find X9 Pro, reducing overall clarity in the image and softening some details. The Xiaomi 17 Pro Max, VIVO X300 Pro, and HONOR Magic8 Pro maintained stronger subject definition, although the HONOR model continued to exhibit a more processed overall look.
Among the five devices, the OPPO Find X9 Pro showed a noticeable drop in crispness due to flare, while the iPhone 17 Pro delivered the softest backlit result overall.

Conclusion

Across both scenes, the five flagship smartphones demonstrated competent performance, but they also exhibited clearly different rendering styles that reflect each manufacturer’s design choices. Xiaomi, vivo and OPPO tended to deliver brighter and more detailed subject representation, making their results appealing to those who prefer a clear and defined look. HONOR leaned toward a more processed aesthetic that may suit users who enjoy a stylized portrait effect. Apple’s iPhone 17 Pro produced softer and darker results in challenging backlit situations, offering a more subdued interpretation of the scene. These distinctions highlight how each device prioritizes different aspects of image creation, helping users select the smartphone that best aligns with their visual preferences and typical shooting conditions.

We will  continue to dive into the performance of these newly released flagships by testing these in additional real world scenarios. Stay tuned!

The post A Closer Look at China’s Latest Flagships: Portraits and Backlit Camera Performance appeared first on DXOMARK.

We previously examined smartphone features that are dependent on ambient Correlated Color Temperature (CCT) that are quickly becoming standard across flagship smartphones. In our initial article on CCT Adjustment Technology (CCT), we highlighted a key industry challenge: smartphones handle color rendering very differently depending on ambient light. This lack of consensus results in varied, and sometimes inconsistent, visual outputs across devices and environments.

Our observations led us to another question: “How do smartphones render the reality we see?”

In other words, to what extent do captured photos reflect the real-life scenes they were taken in? And how much of what users perceive comes not only from the camera, but also from the display?

To explore these questions, we designed a set of experiments examining the so-called “glass-to-glass experience” which can be defined as the full imaging journey from capture through the camera lens and optics (glass) to rendering on the display panel (glass).

The aim of these experiments was to investigate how consistent the smartphone experience is from capture to display.

To do so, we put five flagship smartphones to the test: the iPhone 16 Pro Max, Samsung Galaxy S24 Ultra, Huawei Pura 70 Ultra, Vivo X200 Pro, and Honor Magic 7 Pro. Testing was conducted under both controlled laboratory conditions and real-world scenarios, allowing us to assess the entire imaging pipeline, from photo capture to on-device display rendering under real and ideal laboratory situations.

The experiment was divided into three parts:

• • Camera performance: examining HDR photo capture fidelity to the real scene
  • Display performance: analyzing how images are rendered on device screens
  • Camera to display user experience: studying how a small group of participants perceive fidelity and preference directly on smartphones

Camera capture: a variety of renderings

In this first phase of our experiment, we focused on the analysis of HDR photo capture performance applying our standardized camera testing protocol (learn more here). These included assessments on an HDR monitor (an Apple Pro XDR Display) under calibrated reference lighting conditions to ensure perceptual accuracy.

Entire imaging pipeline captured at the scene, lowlight environment

Perceptual evaluation using standardized visualization conditions

Captures viewed on a standard HDR screen under standardized visualization conditions

Comparing simultaneously the captures on the same reference display, we detected meaningful differences in the accuracy of scene reproduction only imputable to the capture process. For scenes shot in low-light conditions in particular, several challenges emerged that could noticeably affect perceived image quality.

Visualizing the set of pictures on an HDR screen, we observed important issues on some of the pictures taken:

• • Inconsistent white balance
  • Unnatural skin tones
  • In some cases, unbalanced exposure between subject and background
  • And even, for a few flagships a lack of HDR support impacting the rendering

These shortcomings varied across the devices tested, (Apple iPhone 16 Pro Max, Huawei P70 Ultra, Honor Magic 7 Pro, Samsung Galaxy S24 Ultra, and Vivo X200 Pro) highlighting the diverse approaches OEMs take in HDR imaging.

Yet the story does not end with camera capture. The way an image is displayed can amplify or mitigate these capture-related limitations, ultimately shaping user perception.

Display playback: disparities in luminance and color strategies

To assess rendering quality of the tested displays, we loaded two test images on the flagship devices:

1. 1. An SDR photo captured with a DSLR camera
   2. An HDR photo captured with a smartphone (converted into an HDR  format that was compatible across all devices)

SDR photo captured with a DSLR camera, displayed on each smartphone under in low-light conditions that replicates those of the original scene

HDR photo captured with a smartphone, displayed on each device under in low-light conditions that replicates those of the original scene

The goal was to evaluate the difference in rendering on each display for the same input content. Testing was conducted in a controlled lab environment under lighting conditions designed to replicate the original scenes. Detailed luminance and color measurements allowed us to analyze each device’s display behavior with precision.

These findings highlight clear differences in luminance tuning strategies. Brightness levels varied significantly, affecting both readability and overall clarity.

The Huawei Pura 70 Ultra, for example, boosted highlights more aggressively than its peers in both SDR and HDR renderings. Other devices, while appearing dimmer overall, relied on local tone mapping to preserve visibility of key details

Color accuracy was equally distinctive

Noticeable shifts were observed across devices, and users are more sensitive to these changes than they might realize. Each OEM deployed its own ambient light adaptation method. Apple’s iPhones, for instance, dynamically adjusted white balance to match environmental conditions, often leaning towards warmer tones under warm low-light environments.

The key takeaway of this study is that display rendering extends beyond simple image reproduction. It is fundamentally about contextual adaptation. The result is not a direct mirror of reality, but a perceptual experience shaped by both device design and viewing conditions. As perception varies with the environment, the visual impression does as well, reinforcing the need for holistic testing approaches that consider the entire imaging pipeline.

Evaluating Smartphone Glass to Glass User Experience: From Reality to Preference

To better understand how users perceive smartphone camera performance, we conducted a focused study with a small group of European participants. The goal was to evaluate the perceived fidelity and preference of image renderings directly on smartphones, moment after the capture. The experiment took place in-situ, meaning that participants evaluated photos directly in the same environment where they were taken.

Two complementary evaluation methods were used.

• • First, each participant provided an individual assessment by answering: “How close is the rendering to reality?” on a 1–5 scale.
  • Second, a side-by-side comparison was conducted, where participants selected the rendering that looked closest to reality and the one furthest from reality.

Figure 3: side-by-side evaluation

Figure 4: individual evaluation

The results showed a nuanced picture. In the individual evaluation: The Vivo X200 Pro, the iPhone 16 Pro Max and Huawei P70 Ultra were rated as close to reality overall. In contrast, the Honor Magic7 Pro was consistently considered the least faithful both individually and in side-by-side comparisons.

To extend our understanding beyond fidelity, the experiment was repeated with a new focus: user preference. Participants were asked: “How do you like the rendering?” (1–5 scale) and in side-by-side mode, they were instructed to select their most preferred and least preferred rendering.

Interestingly, the findings diverged from the fidelity-focused evaluation. The iPhone 16 Pro Max emerged as the most preferred device in side-by-side comparisons, followed by the Vivo X200 Pro. While the Vivo had previously been considered the most accurate, the iPhone was slightly more appreciated by participants overall. Once again, Honor Magic 7 Pro ranked last, being both the least preferred and the least faithful to reality.

These two complementary rounds of evaluation revealed two key insights.

• • A perceived faithful reproduction of reality is not necessarily the most preferred rendering. Subtle image processing choices, such as contrast or color enhancement, may influence preference even if they deviate from real-life perception.
  • There is a clear correlation between the least faithful and the least preferred rendering, as seen with Honor Magic 7 Pro.

Taken together, these insights illustrate that user experience in smartphone photography sits at the intersection of accuracy and appeal, underlining the importance of balancing fidelity and enhancement in imaging pipeline design comprising camera and display. Further studies are currently being conducted to better understand the preferences.

What does it take to get a good Glass to Glass Experience?

Delivering a unique camera-to-display experience on a smartphone requires the interplay of several critical components working in harmony.

At the foundation is the ambient light sensor (ALS), a small but essential element that constantly measures the surrounding lighting conditions. Manufacturers such as ams OSRAM, a leader in optical sensing technologies, produce advanced ALS solutions that enable this precise environmental awareness. Spectral ALS variants, in particular, enable precise measurements of chromaticity and illuminance (lux), allowing devices to adapt image capture and display playback to the ambient environment. These sensors are typically integrated on both the camera and display sides of the device.

The camera then takes on the task of capturing photos and videos, but the raw image is only the starting point. Through sophisticated image processing, each manufacturer applies its own stylistic choices, enhancing details, balancing exposure, and adjusting color reproduction to create a signature visual identity.

Once the content is captured, the display becomes the final stage of the pipeline, responsible for rendering the image or video back to the user. Here again, adaptation plays a crucial role, as the display fine-tunes brightness, contrast, and color balance to match the ambient light, striving to maintain both clarity and comfort across diverse conditions, from dim interiors to bright outdoor sunlight.

What ultimately defines the user experience, however, is not just the individual performance of these components but the way they are tuned to work together. The subtle choices made in calibration and tuning can elevate the experience, making visuals feel vivid and lifelike, or conversely undermine it, leaving them flat or unrealistic. This fine balance makes tuning a decisive factor in shaping user perception.

Conclusion

Ultimately, our findings highlight the importance of evaluating the entire imaging pipeline as a whole, from ambient light sensing to camera capture and display rendering, because this is how users actually experience their smartphones. Testing components in isolation cannot fully explain how fidelity and preference interact once everything comes together in the user’s hands.

Beyond the technical aspects, many studies also underline that preferences are not universal: they are deeply rooted in culture, habits, and regional aesthetics. A rendering style that appeals to European users may not resonate the same way in Asia or North America. This is why local evaluations are critical, ensuring that tuning strategies are adapted to specific user groups.

By embracing both technical accuracy and cultural sensitivity, manufacturers can better align their devices with real-world user perception and deliver experiences that feel both authentic and engaging.

In addition, as much as smartphones today are recognized for their distinctive “camera signatures”, reflecting each manufacturer’s unique approach to exposure, color balance, and tone, we may now be entering an era of the “display signature.” Beyond capture, the way a device presents content on screen can be just as defining. Some smartphones favor darker brightness adaptation in low light, giving a more cinematic, subdued experience, while others embrace highly vivid color rendering, creating instantly recognizable visuals across their product lines. Ultimately, crafting a meaningful display signature requires a deep understanding of the visual scene and context, enabling the device to apply the most relevant settings and parameters to deliver a consistent, intentional viewing experience, one that becomes as characteristic as its camera output.

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In 2022, DXOMARK conducted a benchmark study of doorbell security cameras. Today, we return with a broader and more comprehensive evaluation, extending the scope to include a wider range of products, covering not only doorbells, but also indoor and outdoor security cameras.

While all security cameras serve the same fundamental purpose, allowing users to see what’s happening in and around their homes, the requirements and expectations vary depending on the product category. In this benchmark we assess each type of camera separately, highlighting their specific use cases, strengths and limitations.

As with all DXOMARK protocols, our evaluation combines rigorous laboratory testing with perceptual analysis in real-world scenarios. The scores rely on objective tests generated by measurement software under controlled lab setups for and on perceptual tests in which a sophisticated set of metrics allow a panel of image experts to compare aspects of image quality that require human judgment. Please note that our tests covered only the image quality, not the overall performance of the doorbell (such as the quality of the Wi-Fi connection, latency…)

In this article, we present a benchmark comparing the performance of devices across different categories.

Doorbell Cameras

From left: Google Nest Doorbell (wired, 3rd gen), Kasa Smart Doorbell (KD110), Wyze Video Doorbell V2, Arlo Video Doorbell 2K, Tapo smart Video Doorbell, Ring Doorbell Pro 2

For doorbell cameras, the primary user expectation is clear: the ability to reliably identify who is at the door, whether it’s broad daylight, dusk, or nighttime. This requires accurate exposure in a variety of conditions: bright sunlight, backlit scenes, and low light. Effective recognition also depends on capturing fine details, from facial features to textures, such as brand logos, badges, or even text on packages.

As noted, doorbell cameras were the focus of a dedicated benchmark published in 2022. In this updated study, we revisit the category with six of the latest models. Each was tested using a dedicated version of our camera protocol, tailored to doorbell use cases. We evaluated their performance across a range of lighting conditions, from day to night, while accounting for dynamic scenes and varying subject distances.

Here are their respective specifications of the models tested:

To provide accuracy and perspective, we’ve added actual images of the field of view, illustrating what you will genuinely see through the camera:

Wyze Video Doorbell V2

Tapo Smart Video Doorbell Wired (Tapo D130)

Ring Doorbell Pro 2

Kasa Smart Doorbell (KD110)

Google Nest Doorbell (Wired, 3rd Gen)

Arlo Video Doorbell 2K

Taking into account all measured metrics across both daylight and nighttime scenarios, the benchmark results below present the performance ranking of all evaluated models.

Daylight use case results

Let’s dive into the results of the doorbell under the daylight use case. Daylight use cases range from well-lit conditions on a sunny day to a strong backlit situation, passing by a cloudy day. Doorbells must adapt to these situations to be usable anytime and in any situation. The chart below reflects the Daylight use case scores for all the tested models.

To dive into more details, if we look at a specific scene like bright sunlight with no porch or cover, identifying typical SDR conditions, we observe that most tested devices performed well in this relatively simple case, delivering properly exposed faces.

The main challenge lies in simultaneously managing background exposure to ensure surroundings remain visible. Here, Google Nest Doorbell distinguished itself, thanks to its HDR implementation (the only device in our benchmark showing HDR capabilities ) avoiding clipping in both highlights and shadow areas. Competing models often clipped bright areas (most often, the sky’s brightest parts)

Google Nest Doorbell – Good brightness on the face, no clipping in bright or dark areas

Tapo Smart Video Doorbell Wired – Acceptable Face brightness, clipping in the sky

Kasa Smart Doorbell (KD110) –  Acceptable face brightness, clipping in both bright and dark areas

When looking at more challenging situations, when the camera is placed under a porch (looking toward street or backyard), this scenario proved more difficult for the devices of the benchmark. Indeed, faces often fall into shadow, making recognition more challenging. Cameras needed to brighten subjects sufficiently while maintaining usable background exposure.

In these scenarios, Google Nest Doorbell again performed strongly, delivering the highest target exposure and balancing face readability with HDR-preserved background detail. Tapo, offered the brightest face exposure but clipped highlights, while other models struggled to maintain a usable balance.

Google Nest Doorbell

Acceptable brightness on face and no clipping in bright or dark areas

Tapo Smart Video Doorbell

Good brightness on face and clipping in the sky

Wyze Video Doorbell Pro 2

Low brightness on face and clipping in both bright and dark

In both daylight setups, detail rendering and low artifact levels were also crucial for identification. Ring and Tapo offered the sharpest details, while Wyze and Google Nest doorbell produced softer textures, often losing small details. Arlo was hampered by compression artifacts. Google Nest doorbell occasionally showed some HDR-related artifacts but these did not hinder recognition.

Night use case results

At night, most devices switch to infrared (IR) mode, often with a built-in IR illuminator. To simulate realistic conditions, we tested cameras under porch-light scenarios, where bright subjects contrasted sharply with dark backgrounds. This often caused clipped facial details, making recognition difficult.

Here again, Google Nest Doorbell’s HDR strategy provided a clear advantage, avoiding or minimizing clipping while maintaining background visibility. Google Nest doorbell also preserved a higher level of detail at night compared to its daytime performance. However, its HDR algorithm introduced noticeable fusion artifacts in IR mode.

Google Nest Doorbell- face is partly clipped but recognizable, background is clearly visible

Ring Wired Doorbell Pro 2 – face fully clipped, background is visible

Kasa Smart Doorbell (KD110)- face partly clipped but recognizable and some background clipping in dark areas

Overall pros & cons of each model

Conclusion

Thanks to its HDR strategy and consistent detail preservation across conditions, Google Nest Doorbell offers the most reliable user experience in our benchmark. Combined with vivid and natural color rendering, it stands out from the competition and earns our DXOMARK Gold Label as the best doorbell camera of 2025.

Outdoor Cameras

From left: Arlo Pro 5 2K, Eufy Security Outdoor Cam E220, Google Nest Cam Outdoor (Wired, 2nd Gen), Ring Outdoor Cam, Wyze Battery Cam Pro

As this category enters our benchmark for the first time, it’s important to note that while the core requirement remains the same, allowing users to see what’s happening around their property, the perspective and use cases differ. Unlike doorbell cameras, which capture visitors directly at the doorstep, outdoor cameras are typically installed higher up or to the side, offering a broader field of view. Their role is less about face-to-face interaction and more about general surveillance, such as monitoring cars entering the driveway or children playing in the yard.

When looking at outdoor security cameras, there are several aspects to consider and to look for. Field of view (FOV) is crucial. From a usability perspective, the wider the coverage, the fewer cameras you will need to monitor your property effectively. Exposure handling is equally important, as the camera must reveal details in both bright and dark areas of the scenes, ensuring that nothing is missed. Finally, texture rendering plays a critical role in identification tasks, such as recognizing unusual activity or reading license plates, which often require maintaining clarity even at long distances.

For the evaluation of outdoor cameras, we considered 5 different models :

To provide accuracy and perspective, we’ve added actual images of the field of view, illustrating what you will genuinely see through the camera:

Ring Outdoor Cam

Google Nest Cam Outdoor (Wired, 2nd Gen)

Eufy Security Outdoor Cam E220

Arlo Pro 5 2K

Wyze Battery Cam Pro

Taking into account all measured metrics across both daylight and nighttime scenarios, the benchmark results below present the performance ranking of all evaluated models.

Specifically looking at the specification of the Field-of- View, the Google Nest Cam Outdoor (wired, 2nd gen) delivers a wide lateral field of view, comparable to most models currently available on the market. Among the other models of our benchmark, Ring stands out with the broadest lateral coverage while Wyze offers the narrowest.

Daylight use case results

Let’s dive into the results of the doorbell under the daylight use case. As for doorbells, daylight use cases range from well-lit conditions on a sunny day to a strong backlit situation, passing by a cloudy day. In addition, specific use cases such as license plate readability as well as ball play in the background were specifically studied.

Our results indicate that in daylight conditions, all tested devices provide accurate face exposure under standard SDR scenarios. The Google Nest Cam Outdoor stands out in high-dynamic-range situations, delivering the widest dynamic range and avoiding clipping in both bright areas (such as the sky) and shadows, a challenge for most competing models. At closer distances, Google Nest Cam Outdoor consistently offers the highest level of detail, only occasionally surpassed by Eufy in specific scenes. As the subject moves farther from the camera, identifying a person becomes more challenging for all devices; however, Google Nest Outdoor Cam and Eufy maintain the clearest recognition at longer distances.

Google Nest Cam Outdoor

Accurate exposure, dynamic range and acceptable level of details for face recognition

Ring Outdoor Cam Pro

Low level of details on the face

Arto Pro 5 2K

Low level of details on the face

Night use case results

Similarly to doorbells, to simulate realistic conditions, we tested cameras under porch-light scenarios, using an external light source and not the potentially built-in light of the cameras for a fair evaluation.

Looking at night use cases, the Google Nest Cam Outdoor provides the best overall balance, delivering accurate facial brightness while preserving visibility in the background. Other cameras often struggle, either overexposing faces or losing detail in dark areas, which can limit effective surveillance.

Achieving accurate target exposure in low-light conditions can be challenging, particularly when it comes to controlling noise. Google Nest manages this well, showing only slightly more visible noise than its competitors while still delivering a solid balance for surveillance use cases.

Regarding detail retention, all devices face challenges in low-light conditions; however, the Google Nest Cam Outdoor performs better than most, maintaining enough clarity for faces to remain identifiable at close range.

Google Nest Cam Outdoor
face partly clipped but still recognizable, background remains visible.

Eufy Security Outdoor Cam E220
Face fully clipped though the background is visible

Ring Outdoor Cam
Face fully clipped with additional clipping in dark areas of the background

Overall pros & cons of each model

Conclusion 

Google Nest Cam Outdoor – 1st Place

Ring Outdoor Cam

Thanks to its HDR processing and consistently strong level of detail across all conditions, the Google Nest Outdoor Cam delivers optimized surveillance performance. Combined with its natural and pleasant color rendering, it stands out as the best outdoor camera in our benchmark.

Following the Google Nest Outdoor Cam, the Ring Outdoor Cam also delivers strong overall performance, offering a wide field of view and well-controlled noise. Both devices qualify for the DXOMARK Gold Label for outdoor cameras.

Indoor Cameras

From left: Arlo Essential Indoor Camera (2nd Gen), Eufy Indoor Camera S350, Google Nest Cam Indoor (Wired, 3rd Gen), Ring Outdoor Cam (2nd Gen), Wyze Cam V4

While doorbell and outdoor cameras are primarily focused on monitoring specific events such as intrusions or a vehicle entering the driveway, indoor cameras serve a broader purpose: capturing as much of the room as possible, including windows and general activity within the scene.

When evaluating indoor cameras, several key factors come into play. Field of view (FOV) is critical from a practical standpoint, the wider the coverage, the fewer cameras are needed to monitor the space effectively. Exposure must be balanced, ensuring visibility in both bright and dark areas of the room. Finally, texture rendering is important for identification purposes, allowing intruders or other subjects to be recognized clearly at short to medium distances.

For the benchmark of the indoor cameras, we considered 5 different models, presented below with their respective specifications:

To provide accuracy and perspective, we’ve added actual images of the field of view, illustrating what you will genuinely see through the camera:

Arlo Essential Indoor Camera (2nd Gen)

Eufy Indoor Cam S350

Google Nest Cam Indoor (Wired, 3rd Gen)

Ring Indoor Cam (2nd Gen)

Wyze Cam V4

Taking into account all measured metrics across both daylight and nighttime scenarios, the benchmark results below present the performance ranking of all evaluated models.

Within our benchmark, the Google Nest Cam indoor camera offers the widest lateral field of view, capturing the most area and providing a comprehensive view of the room. In contrast, the Wyze cam v4 has the narrowest coverage, leaving some corners of the room outside its view.

Color mode / Daylight test results 

In this specific part, we will qualify the performance of indoor cameras when light levels are sufficient to use a visible-light sensor.

In daylight conditions, using natural light from windows, overall face brightness is generally accurate. While the Google Nest Cam indoor has a slightly lower target exposure on faces compared to Eufy and Wyze, faces remain easily recognizable. Arlo, by contrast, has the lowest face exposure, making recognition more challenging. Google Nest Cam Indoor’s key advantage over competitors is a wide dynamic range, minimizing clipping in bright areas such as windows and allowing effective monitoring of both subjects and background.

Under “evening” conditions with only dim artificial lighting, Google Nest Cam Indoor maintains the lowest face brightness, yet faces are still fully identifiable.

In terms of detail, Google Nest Cam Indoor provides an acceptable level for recognition, though fine textures appear softer and less sharp compared to Eufy or Wyze. Color rendering and white balance are generally pleasant across most cameras; however, Wyze can appear slightly desaturated, while Arlo exhibits a pronounced orange cast under warm artificial lighting in evening conditions.

Google Nest Indoor
Accurate face exposure, wide dynamic range

Eufy Indoor Cam 350
Accurate face exposure, clipping in bright parts

Ring Indoor Cam 2nd gen
Accurate face exposure, clipping in bright parts

Infrared mode test results 

When light levels are too low for usual cameras to offer an acceptable quality, surveillance devices can switch to Infrared (IR) mode. All cameras in our benchmark offer a black-and-white IR mode.

Most deliver accurate overall brightness, though some lose detail in shadowed areas. The Google Nest Cam Indoor stands out with the widest dynamic range, but its tone compression can sometimes render faces unnaturally, making identification slightly more difficult. It is the only camera that avoids complete clipping of objects near the IR source, allowing at least partial recognition. In terms of detail, Google Nest Cam Indoor provides an acceptable level for face identification, although fine textures are softer and less sharp compared to Eufy or Wyze.

Google Nest Cam Indoor
Accurate face exposure, details appear soft

Arlo Essential Indoor Cam 2nd generation

Slightly low face exposure at longer distances, with noticeable loss of detail

Wyze Cam v4
Accurate face exposure with sharp, well-defined details

Overall pros & cons of each model

Conclusion

Google Nest Cam Indoor (wired, 3rd gen) – 1st Place

eufy Security Indoor Cam S350

Thanks to its HDR strategy and wide field of view, the Google Nest Indoor provides optimized indoor surveillance in all lighting conditions, along with pleasant color rendering and a sufficient level of detail. The Eufy Indoor Cam also offers a good experience, delivering high levels of detail and accurate target exposure. Both devices qualify for the Gold Label for indoor cameras.

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At DXOMARK, the evolution of our protocols is a continuous process, aimed at keeping pace with the accelerating innovation in smartphone imaging. With each generation of devices introducing new technologies and user-centric features, our testing methodologies adapt accordingly, not only to stay up to date but also to ensure our scores remain relevant and meaningful for real-world users.

Today, we officially unveiled the 6th version of our Smartphone Camera Protocol, the most advanced and user-aligned protocol to date. This release is the product of our traditional multi-phase development strategy that reflects both technical rigor and human-centric evaluation.

A methodological framework grounded in real-world use

Each update to our protocol follows a structured methodology built on major key pillars, starting with identifying user needs and preferences, developing representative and repeatable test scenarios, and culminating in the thorough evaluation and scoring of products.

Understanding user needs and preferences

Our foundation lies in in-depth research, including multi-year investigations about user preferences through DXOMARK Insights. These studies, conducted with large panel groups, explore key user pain points, particularly in challenging domains such as HDR portrait photography. Since 2023, we have carried out extensive studies across China, India and Europe, uncovering detailed insights about user expectations in portrait photography.

To enrich this broad understanding, DXOMARK regularly collaborates with independent experts in their fields (photographers, video makers…). Ahead of the launch of our Camera v6 protocol, we are deepening our engagement through the creation of the DXOMARK Expert Committee, a body of professionals and academic experts who provide valuable perspectives on emerging trends and real-world usage scenarios.

Designing representative and repeatable test scenarios

At our state-of-the-art labs in Boulogne-Billancourt, we design tests that mirror real-world usage with scientific precision. Our approach combines objective measurements and perceptual testing, covering a wide range of lighting conditions, motion scenarios, and diverse skin tones. Purpose-built setups and proprietary tools enable us to achieve a new level of granularity in testing. Beyond the lab, we also conduct tests and analyses in varied natural environments. Each device is tested extensively with over 4000 photos captured and 200 minutes of video recorded under a wide range of conditions.

Scoring: The tip of the iceberg

While our scores are publicly visible, they represent just the surface of a comprehensive evaluation process. These scores distill the end-user experience into a clear, comparable format. With the launch of our sixth-generation protocol, we introduce a revamped scoring architecture and weighting system, aligned with an updated testing matrix and newly refined quality metrics.

What’s new in the new version of our protocol?

The sixth version of our protocol introduces updates across three key areas:

• • Enhanced HDR evaluation, featuring a new testing process and refined scoring methodology.
  • Updated portrait testing, informed by recent global studies to better reflect real-world user expectations.
  • Expanded focus on zoom performance, with particular attention to video zoom capabilities.

Now, let’s dive into the details of our protocol updates

Portrait evaluation: adapting to user trends and expectations

Taking portrait photos is one of the most common and emotionally resonant use cases in smartphone photography. Guided by our extensive insights run between 2023 and 2025 in different parts of the world, we identified 3 key elements looked at by users while defining a good portrait picture: a consistently well exposed face and overall picture, natural skin tones as well as an accurate and neutral white balance. We also observed that users were consistently unhappy and still identified challenges when it came to lowlight and nigh photography, which still represented major challenges for users.

These insights provided us with clear guidelines on users’ expectations as well as general trends on preferences, that directly drive our methodology and our tests.

What have we changed in our evaluations?

To better reflect real-world usage, including both everyday and challenging situations, we’ve significantly upgraded our portrait testing protocols:

• • 50 new portrait scenes, covering a full range of lighting conditions, from moonlight to sunlight, captured both in natural environments and simulated lab settings. In total, we now evaluate 9 lighting conditions in photo and 13 in video.
  • A broader spectrum of skin tones, ensuring inclusive and comprehensive evaluation across diverse subjects.
  • Three motion profiles, simulating real user behavior, from static handheld shooting (two-handed grip) to walking scenarios (for video), to test performance in typical portrait capture situations.

Our tools and test methods have evolved to deliver deeper, more meaningful insights into image quality. At the core of this is our newly developed All-in-One Portrait Lab setup, powered by Analyzer, designed to simulate real-world challenges in a controlled environment. It includes:

• • Two high-fidelity mannequins representing deep and fair skin tones, used to assess facial detail preservation.
  • Dynamic lighting simulation, covering a wide range from 0.1 lux to 10,000 lux, to evaluate performance under various illumination levels.
  • Motion simulation tools, including moving objects, a hexapod (six-axis motion platform), and a time box to rigorously test autofocus accuracy and motion blur.
  • Reflective and transmissive gray scales, supporting in-depth analysis of noise and contrast behavior.

To complete the evaluation of portraits, we now run a systematic perceptual evaluation of flare, which can affect facial clarity and background rendition.

HDR: A consistent evaluation of the HDR formats

As outlined in our recent publications, HDR is reshaping the landscape of smartphone photography. As brands explore various approaches to HDR integration (see our China Insights), new creative opportunities are emerging, alongside fresh technical challenges. The evolution of HDR formats now includes standardized versions that are compatible across a wide range of smartphones, ensuring more consistent user experiences.

To reflect the growing importance of HDR, we have now integrated a dedicated and systematic evaluation of HDR performance into our testing protocol, applicable when the tested device supports a publicly documented format that is compatible with common HDR viewing tools. This enhancement ensures a more accurate and comprehensive understanding of how HDR impacts image quality across devices.

It includes:

• • Expanded HDR scenes coverage: our testing now includes a broader range of natural scenes (across all lighting conditions, including night scenes) as well as in controlled lab environments using our AF-HDR setup.
  • New lab-based metrics: Additional objective measurements offer finer granularity in assessing HDR performance under reproducible conditions.
  • Perceptual analysis with professional reference HDR display: Evaluations are conducted using our AQuA tool (which brings an objective perspective on perceptual analysis) on an ISO 22028-5 reference HDR monitor.

When a supported HDR format is detected, images are processed with the appropriate gain maps and evaluated through our HDR visualization pipeline using dedicated scoring criteria. If the image is in a non-HDR format or an unsupported HDR format, it is analyzed as an SDR image using the same tools, ensuring consistency and fairness across all devices.

Zoom: An increased focus on growing user features

Zoom capabilities have emerged as a key differentiator among flagship smartphones. Increasingly valued by users, zoom is now widely used across a variety of scenarios, from close and mid-range portraits to long-range landscape and wildlife photography. In recent years, we’ve observed significant advancements across devices, enabling users to capture high-quality images even in the most demanding conditions.

In response to evolving user behavior, we have redefined our zoom testing protocol with a stronger emphasis on emerging use cases, such as video zoom, which is increasingly used during live events and concerts to capture subjects from a distance.

Key evolutions in our testing include:

• • A focus on the 85–300mm zoom range, which is especially relevant for medium to long-range portrait photography.
  • Simulation of user motion
  • Evaluation criteria covering a broad set of attributes: from static elements like face exposure, contrast, dynamic range, and texture, to temporal aspects such as stabilization and autofocus consistency, as well as usability metrics like zoom smoothness.

While we’ve refined our protocol for close- to medium-range zoom, representing most of everyday use cases, ultra zoom (200 mm and beyond) continues to be evaluated through a dedicated protocol. We’ll soon publish updated results from this specialized testing.

Video: Simulating Real-Life Movement and Light

Smartphone video performance has advanced significantly in the past few years with results now getting closer to professional standards. Videos are now marked with significantly richer color, enhanced contrast and greater detail. For the past eight years, devices like the Apple iPhone have consistently set the benchmark for mobile video quality, delivering reliable performance and excellent detail retention across a wide range of lighting conditions.

To stay aligned with the rapid advancements in smartphone videography, we have significantly updated our evaluation protocols. In the sixth version of our video testing protocol, we’ve introduced several key enhancements:

• • Simulated user motion in the lab: We are the first to incorporate a protocol that evaluates video quality using captures recorded under controlled, simulated user movement bringing greater realism and reproducibility to our tests.
  • Broader range of use cases: We’ve expanded scene diversity to include a wider variety of skin tones, better reflecting real-world usage.
  • Extended lighting scenarios: Our automated lab setup now covers four distinct lighting levels (from 5 to 1000 lux), each paired with systematic HDR scene simulations. Additionally, we’ve implemented a dedicated night-shooting plan, designed to evaluate performance across a variety of low-light situations and user scenarios.

Revised Architecture and Scoring System

In the latest version of our protocol, we have revised the scoring methodology to provide a more detailed and user-relevant evaluation of device performance. The updated framework now includes two main sub-scores: Photo and Video, each assessing the performance of the device’s primary focal lengths: main, tele, and ultra-wide.

This structure offers a clearer view of how each focal length performs in both still and motion capture. Additionally, we’ve introduced use-case scores to reflect real-world scenarios, providing insights into the device’s capabilities in specific contexts such as portrait photography, zoom performance (across both photo and video), and low-light shooting—a persistently challenging condition identified in our previous research.

Initial Results from Camera v6 protocol

With the new protocol version comes an updated camera ranking, resulting in some shifts in smartphone positions compared to previous rankings.

To give you a clearer idea of what to expect, this section presents an overview of the evaluation of three popular devices.

Apple iPhone 16 Pro Max

In our Camera v6 protocol, the iPhone 16 Pro Max is mostly impacted in our Photo score. Indeed, while fine noise has a reduced impact compared to earlier versions, faces frequently appear underexposed. This lower brightness is generally less appreciated by users, resulting in a greater negative impact on perceived exposure quality.

Highlights on the performance of the product evaluated under the v6 Camera protocol:

• • Portrait: in our new protocol, the iPhone 16 Pro Max remains an excellent choice for portrait pictures, whether capturing a single person or a group on the same focal plane. Thanks to effective HDR management, portrait images appear immersive, vibrant and visually appealing.
  • Zoom Video: Video continues to be a strong area for the iPhone 16 Pro Max under our new testing protocol. When analyzing zoom performance during video recording, the device delivers smooth transitions and maintains high image quality throughout the zoom range.
  • Lowlight: With the inclusion of more low-light and challenging scenes in our protocol, the iPhone 16 Pro Max continues to perform strongly in photo mode while remaining the top performer in video. It produces bright images with a wide dynamic range, preserving both detail and contrast even in difficult lighting conditions.

Xiaomi 15 Ultra

Under our Camera v6 protocol, the Xiaomi 15 Ultra benefits from the increased emphasis on portrait color and telephoto zoom performance, resulting in a higher ranking.

Highlights on the performance of the product evaluated under the v6 Camera protocol:

• • Portrait: in our new protocol, the Xiaomi 15 Ultra was capable of capture nice portraits with realist skin tones and good exposure across all lighting conditions.
  • Zoom photo & video: The Xiaomi 15 Ultra delivers a strong performance in telephoto, keeping a high level of detail and sharpness across the entire zoom range. It also performs strongly in video zoom, offering stable and clear results.
  • Lowlight: The device provides good low-light imaging experience, featuring a warm white balance that preserves the ambient atmosphere, along with impressive noise reduction.

Samsung Galaxy S25 Ultra

In our new protocol, the Samsung Galaxy S25 Ultra is mostly impacted by the lower impact on noise and the growing weight of telephoto zoom.

Highlights of the performance of the product evaluated under the v6 Camera protocol:

• • Portrait: The Samsung Galaxy S25 Ultra delivers strong portrait photography performance across default, bokeh, and tele modes, with good subject detail, accurate edge detection, and versatile features like realistic blur effects and adjustable lighting.
  • Zoom: The Samsung Galaxy S25 Ultra offers impressive telephoto performance with sharp, detailed images across medium to long zoom ranges, supported by fast and reliable autofocus. While it delivers strong overall quality, some softness and noise appear at extreme zoom levels, placing it just behind top competitors like the Oppo Find X8 Ultra and Xiaomi 15 Ultra.
  • Lowlight: In low-light conditions, the camera generally delivered good exposure and accurate white balance, though occasional underexposure and unnatural tones were observed. Testers also noted inconsistencies in noise and detail between shots, highlighting a lack of consistency in performance across challenging lighting conditions.

Conclusion

With the launch of DXOMARK’s sixth-generation Smartphone Camera Evaluation Protocol, we reaffirm our commitment to providing the most accurate, relevant, and user-centric assessments in the mobile imaging space. By integrating cutting-edge testing tools, global user insights, and real-world use cases into our methodology, Camera v6 marks a significant step forward in how smartphone camera performance is measured. As innovation in mobile photography accelerates, this new protocol ensures our rankings remain not only scientifically robust but also truly reflective of the everyday experiences and expectations of users worldwide.

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