We put the Google Pixel 11 Pro XL through our rigorous DXOMARK Selfie test suite to measure its performance in photo and video from an end-user perspective. This article breaks down how the device fared in a variety of tests and several common use cases and is intended to highlight the most important results of our testing with an extract of the captured data.
Overview
Key front camera specifications:
- 42 MP Dual PD selfie camera with autofocus
- f/2.2-aperture lens
- 103° ultra-wide field of view
Scoring
Sub-scores and attributes included in the calculations of the global score.
Google Pixel 11 Pro XL
151
selfie
97
Apple iPhone 16 Pro Max
Best: Apple iPhone 16 Pro Max (99)
108
Google Pixel 9 Pro XL
Best: Google Pixel 9 Pro XL (110)
97
Apple iPhone 17 Pro
Best: Apple iPhone 17 Pro (105)
70
Asus ZenFone 7 Pro
Best: Asus ZenFone 7 Pro (79)
69
Huawei Mate 50 Pro
Best: Huawei Mate 50 Pro (94)
88
Apple iPhone 16 Pro Max
Best: Apple iPhone 16 Pro Max (91)
89
Huawei Mate 50 Pro
Best: Huawei Mate 50 Pro (93)
80
Samsung Galaxy S26 Ultra
Best: Samsung Galaxy S26 Ultra (85)
86
Apple iPhone 17 Pro
Best: Apple iPhone 17 Pro (89)
88
Apple iPhone 15 Pro
Best: Apple iPhone 15 Pro (90)
90
Apple iPhone 17 Pro
Best: Apple iPhone 17 Pro (95)
87
Asus ZenFone 6
Best: Asus ZenFone 6 (97)
79
Xiaomi Mi 11 Ultra
Best: Xiaomi Mi 11 Ultra (83)
88
Apple iPhone 12 mini
Best: Apple iPhone 12 mini (92)
84
Apple iPhone 17 Pro
2nd
2. Apple iPhone 16 Pro Max
151
2. Google Pixel 11 Pro XL
151
5. Apple iPhone 15 Pro Max
149
8. Apple iPhone 14 Pro Max
145
15. Samsung Galaxy S26 Ultra
142
18. Samsung Galaxy S23 Ultra
141
23. Samsung Galaxy S20 Ultra 5G (Exynos)
137
25. Samsung Galaxy Note20 Ultra 5G (Exynos)
136
27. Samsung Galaxy S22 Ultra (Exynos)
135
27. Samsung Galaxy S21 Ultra 5G (Exynos)
135
27. Samsung Galaxy Note20 (Exynos)
135
30. Apple iPhone 13 Pro Max
134
30. Samsung Galaxy Note 10+ 5G (Exynos)
134
35. Samsung Galaxy S21 Ultra 5G (Snapdragon)
133
36. Apple iPhone 12 Pro Max
132
36. Samsung Galaxy S21 5G (Exynos)
132
42. Samsung Galaxy S10 5G (Exynos)
130
42. Samsung Galaxy Note20 Ultra 5G (Snapdragon)
130
44. Samsung Galaxy S10+ (Exynos)
129
47. Samsung Galaxy S21 FE 5G (Snapdragon)
127
56. Apple iPhone 11 Pro Max
122
56. Honor Magic4 Ultimate
122
60. Vivo X60 Pro 5G (Snapdragon)
119
69. Huawei Mate 30 Pro 5G
112
72. Samsung Galaxy Z Flip
111
73. Apple iPhone SE (2020)
110
83. Xiaomi Mi CC9 Pro Premium Edition
100
96. Samsung Galaxy Z Fold3 5G
83
2nd
2. Apple iPhone 16 Pro Max
151
2. Google Pixel 11 Pro XL
151
5. Apple iPhone 15 Pro Max
149
8. Apple iPhone 14 Pro Max
145
14. Samsung Galaxy S26 Ultra
142
17. Samsung Galaxy S23 Ultra
141
20. Samsung Galaxy S20 Ultra 5G (Exynos)
137
21. Samsung Galaxy Note20 Ultra 5G (Exynos)
136
22. Samsung Galaxy S22 Ultra (Exynos)
135
22. Samsung Galaxy S21 Ultra 5G (Exynos)
135
22. Samsung Galaxy Note20 (Exynos)
135
25. Apple iPhone 13 Pro Max
134
25. Samsung Galaxy Note 10+ 5G (Exynos)
134
28. Samsung Galaxy S21 Ultra 5G (Snapdragon)
133
29. Apple iPhone 12 Pro Max
132
31. Samsung Galaxy S10 5G (Exynos)
130
31. Samsung Galaxy Note20 Ultra 5G (Snapdragon)
130
33. Samsung Galaxy S10+ (Exynos)
129
40. Apple iPhone 11 Pro Max
122
40. Honor Magic4 Ultimate
122
47. Huawei Mate 30 Pro 5G
112
48. Samsung Galaxy Z Flip
111
56. Samsung Galaxy Z Fold3 5G
83
Pros
- Accurate target exposure with pleasant contrast on the face in photo, and generally accurate and stable exposure with a wide dynamic range in video.
- Pleasant color rendering with natural white balance in photo, and generally pleasant colors with natural skin tones in video.
- Fairly high level of detail in bright conditions in photo, with high texture levels particularly in outdoor and indoor conditions in video.
- Accurate and stable autofocus in photo.
- Accurate depth estimation with pleasant overall segmentation in photo bokeh.
- Effective video stabilization during both stillness and walking.
Cons
- Low level of detail in photo under low-light conditions, with some details appearing unnatural on skin.
- Some white balance casts are visible in photo under low-light conditions.
- Slightly limited depth of field in photo, affecting group pictures.
- Skin texture can sometimes be overdetailed, with slight hue shifts visible in photo.
- Temporal noise is quite visible on faces in video under low-light conditions and in some backlit scenes.
- Some moving texture is sometimes visible in video.
The Google Pixel 11 Pro XL delivers a strong overall selfie experience, with reliable results in both photo and video. The front camera generally provides accurate exposure with pleasant contrast on faces, while color rendering remains natural across most tested conditions. Detail levels are also fairly high in bright conditions, and autofocus is generally accurate and stable, making the camera reliable for everyday selfies and group shots.
Portrait selfies are another positive aspect, with accurate depth estimation and generally pleasant subject segmentation. The camera is able to separate the subject from the background effectively, although the limited depth of field can become a constraint when taking group selfies. In more difficult conditions, particularly lowlight, the rendering becomes less convincing, with reduced detail levels, some unnatural skin texture and occasional white balance casts.
Video selfies provide an equally solid experience, particularly in outdoor and indoor conditions. The camera maintains a high level of texture while providing generally accurate and stable exposure, with a wide dynamic range that helps preserve information across the scene. Colors are pleasant with natural skin tones, and stabilization is effective both when remaining still and while walking. Lowlight video remains more challenging, with visible temporal noise on faces and occasional moving-texture artifacts.
Google Pixel 11 Pro XL Selfie Scores vs Ultra-Premium
This graph compares overall photo and video DXOMARK Selfie scores between tested devices and references. Average and maximum scores of the price segment are also indicated. Average and maximum scores for each price segment are computed based on the DXOMARK database of devices.
Test summary
About DXOMARK Selfie tests: For scoring and analysis, DXOMARK engineers capture and evaluate more than 1,500 test images both in controlled lab environments and in outdoor, indoor and low-light natural scenes, using the front camera’s default settings. The photo protocol is designed to take into account the user’s needs and is based on typical shooting scenarios, such as close-up and group selfies. The evaluation is performed by visually inspecting images against a reference of natural scenes, and by running objective measurements on images of charts captured in the lab under different lighting conditions from 1 to 1,000+ lux and color temperatures from 2,300K to 6,500K. For more information about the DXOMARK Selfie test protocol, click here. More details on how we score smartphone cameras are available here. The following section gathers key elements of DXOMARK’s exhaustive tests and analyses .Full performance evaluations are available upon request. Please contact us on how to receive a full report.
Photo
146
Apple iPhone 17 Pro
Apple iPhone 17 Pro
Google Pixel 11 Pro XL Photo scores vs Ultra-Premium
The photo tests analyze image quality attributes such as exposure, color, texture, and noise in various light conditions. Range of focus and the presence of artifacts on all images captured in controlled lab conditions and in real-life images are also evaluated. All these attributes have a significant impact on the final quality of the images captured with the tested device and can help to understand the camera’s main strengths and weaknesses.
In photo mode, the Google Pixel 11 Pro XL delivers generally accurate target exposure with pleasant contrast on faces. Color rendering is pleasant in most conditions, with a natural white balance contributing to a balanced and natural-looking rendering. The camera also preserves a fairly high level of detail in bright conditions, while autofocus is often accurate and stable, helping maintain consistent results across a variety of scenes.
The bokeh mode offers accurate depth estimation and generally pleasant subject segmentation, allowing the camera to produce convincing portraits with a natural separation between the subject and the background. However, performance becomes less consistent in low-light conditions, where the level of detail decreases and some details on skin can appear unnatural. Some white balance casts are also visible in low light, while skin texture can sometimes appear overly detailed and slight hue shifts can affect skin tone rendering. The slightly limited depth of field can additionally affect group pictures.
Exposure
97
Apple iPhone 16 Pro Max
Apple iPhone 16 Pro Max
Google Pixel 11 Pro XL – Nice exposure and contrast on the face
Google Pixel 10 Pro XL – Nice exposure, lower contrast
Apple iPhone 17 Pro – Slightly lower face exposure
Color
108
Google Pixel 9 Pro XL
Google Pixel 9 Pro XL
Exposure and color are the key attributes for technically good pictures. For exposure, the main attribute evaluated is the brightness of the face(s) in various use cases and light conditions. Other factors evaluated are the contrast and the dynamic range, eg. the ability to render visible details in both bright and dark areas of the image. Repeatability is also important because it demonstrates the camera’s ability to provide the same rendering when shooting consecutive images in a row.
For color, the image quality attributes analyzed are skin-tone rendering, white balance, color shading, and repeatability.
Google Pixel 11 Pro XL – Pleasant color on different types of skin
Google Pixel 10 Pro XL – Pleasant colors but slightly more muted
Apple iPhone 17 Pro – Pleasant colors with a slightly warmer cast
Focus
97
Apple iPhone 17 Pro
Apple iPhone 17 Pro
Autofocus tests evaluate the accuracy of the focus on the subject’s face, the repeatability of an accurate focus, and the depth of field. While a shallow depth of field can be pleasant for a single-subject selfie or close-up shot, it can be problematic in specific conditions such as group selfies; both situations are tested. Focus accuracy is also evaluated in all the real-life images taken, from 30cm to 150cm, and in low light to outdoor conditions.
Texture
70
Asus ZenFone 7 Pro
Asus ZenFone 7 Pro
Texture tests analyze the level of details and the texture of subjects in the images taken in the lab as well as in real-life scenarios. For natural shots, particular attention is paid to the level of details in facial features, such as the eyes. Objective measurements are performed on chart images taken in various lighting conditions from 1 to 1000 lux and different kinds of dynamic range conditions. The charts used are the proprietary DXOMARK chart (DMC) and the Dead Leaves chart.
Texture acutance evolution with the illuminance level
This graph shows the evolution of texture acutance with the level of lux for two holding conditions. The texture acutance is measured on the Dead Leaves chart in the Close-up Dead Leaves setup.
Noise
69
Huawei Mate 50 Pro
Huawei Mate 50 Pro
Noise tests analyze various attributes of noise such as intensity, chromaticity, grain, and structure on real-life images as well as images of charts taken in the lab. For natural images, particular attention is paid to the noise on faces, but also on dark areas and high dynamic range conditions. Objective measurements are performed on images of charts taken in various conditions from 1 to 1000 lux and different kinds of dynamic range conditions. The chart used is the DXOMARK Dead Leaves chart and the standardized measurement such as Visual Noise derived from ISO 15739.
Visual noise evolution with illuminance levels in handheld condition
This graph shows the evolution of visual noise metric with the level of lux in handheld condition. The visual noise metric is the mean of visual noise measurement on all patches of the Dead Leaves chart in the Close-up Dead Leaves setup. DXOMARK visual noise measurement is derived from ISO15739 standard.
Artifacts
88
Apple iPhone 16 Pro Max
Apple iPhone 16 Pro Max
The artifacts evaluation looks at lens shading, chromatic aberrations, distortion measurement on the Dot chart and MTF, and ringing measurements on the SFR chart in the lab. Particular attention is paid to ghosting, quantization, halos, and hue shifts on the face among others. The more severe and the more frequent the artifact, the higher the point deduction on the score. The main artifacts observed and corresponding point loss are listed below.
Main photo artifacts penalties
Bokeh
80
Samsung Galaxy S26 Ultra
Samsung Galaxy S26 Ultra
Bokeh is tested in one dedicated mode, usually portrait or aperture mode, and analyzed by visually inspecting all the images captured in the lab and in natural conditions. The goal is to reproduce portrait photography comparable to one taken with a DSLR and a wide aperture. The main image quality attributes paid attention to are depth estimation, artifacts, blur gradient, and the shape of the bokeh blur spotlights. Portrait image quality attributes (exposure, color, texture) are also taken into account.
Google Pixel 11 Pro XL – Pleasant exposure and color, good segmentation and blur gradient
Google Pixel 10 Pro XL – Pleasant exposure and color, more artifacts on segmentation and blur gradient
Apple iPhone 17 Pro – Pleasant exposure and color, more artifacts on segmentation and blur gradient
About DXOMARK Selfie Video tests
DXOMARK engineers capture and evaluate more than 2 hours of video in controlled lab environments and in natural low-light, indoor and outdoor scenes, using the front camera’s default settings. The evaluation consists of visually inspecting natural videos taken in various conditions and running objective measurements on videos of charts recorded in the lab under different conditions from 1 to 1000+ lux and color temperatures from 2,300K to 6,500K.
Google Pixel 11 Pro XL Video scores vs Ultra-Premium
Video tests analyze the same image quality attributes as for still images, such as exposure, color, texture, or noise, in addition to temporal aspects such as speed, smoothness, and stability of exposure, white balance, and autofocus transitions.
In video mode, the Google Pixel 11 Pro XL delivers a strong selfie experience, with generally accurate and relatively stable target exposure and a wide dynamic range across a range of lighting conditions. Colors are generally pleasant, with natural skin tones contributing to a balanced rendering. Texture levels are high, particularly in outdoor and indoor conditions, allowing the camera to preserve a good amount of detail in well-lit scenes.
Stabilization is also effective during both stillness and walking, helping provide smooth footage in common recording scenarios. However, temporal noise can become quite visible on faces under low-light conditions and in some backlit scenes. Some moving texture is also visible at times, affecting the consistency of detail rendering in video. Overall, the Pixel 11 Pro XL provides a strong and well-balanced selfie video experience, particularly in outdoor and indoor conditions.
Exposure
86
Apple iPhone 17 Pro
Apple iPhone 17 Pro
Color
88
Apple iPhone 15 Pro
Apple iPhone 15 Pro
Exposure tests evaluate the brightness of the face and the dynamic range, eg. the ability to render visible details in both bright and dark areas of the image. Stability and temporal adaption of the exposure are also analyzed. Image-quality color analysis looks at skin-tone rendering, white balance, color shading, stability of the white balance and its adaption when light is changing.
Google Pixel 11 Pro XL – Pleasant exposure and color
Google Pixel 10 Pro XL – Some contrast issues in dynamic scenario
Apple iPhone 17 Pro – Pleasant exposure and color
Texture
87
Asus ZenFone 6
Asus ZenFone 6
Texture tests analyze the level of details and texture of the real-life videos as well as the videos of charts recorded in the lab. Natural video recordings are visually evaluated, with particular attention paid to the level of detail on the facial features. Objective measurements are performed of images of charts taken in various conditions from 1 to 1000 lux. The chart used is the Dead Leaves chart.
Texture acutance evolution with the illuminance level
This graph shows the evolution of texture acutance with the level of lux for two holding conditions. The texture acutance is measured on the Dead Leaves chart in the Close-up Dead Leaves setup.
Noise
79
Xiaomi Mi 11 Ultra
Xiaomi Mi 11 Ultra
Noise tests analyze various attributes of noise such as intensity, chromaticity, grain, structure, temporal aspects on real-life video recording as well as videos of charts taken in the lab. Natural videos are visually evaluated, with particular attention paid to the noise on faces. Objective measurements are performed on the videos of charts recorded in various conditions from 1 to 1000 lux. The chart used is the DXOMARK visual noise chart.
Spatial visual noise evolution with the illuminance level
This graph shows the evolution of spatial visual noise with the level of lux. Spatial visual noise is measured on the visual noise chart in the video noise setup. DXOMARK visual noise measurement is derived from ISO15739 standard.
Temporal visual noise evolution with the illuminance level
This graph shows the evolution of temporal visual noise with the level of lux. Temporal visual noise is measured on the visual noise chart in the video noise setup.
Stabilization evaluation tests the ability of the device to stabilize footage thanks to software or hardware technologies such as OIS, EIS, or any others means. The evaluation looks at overall residual motion on the face and the background, smoothness and jellow artifacts, during walk and paning use cases in various lighting conditions. The video below is an extract from one of the tested scenes.
Google Pixel 11 Pro XL – Efficient stabilization, pleasant exposure and color
Google Pixel 10 Pro XL – Some residual motion, pleasant exposure and color
Apple iPhone 17 Pro – Efficient stabilization
Artifacts
88
Apple iPhone 12 mini
Apple iPhone 12 mini
Artifacts are evaluated with MTF and ringing measurements on the SFR chart in the lab as well as frame-rate measurements using the LED Universal Timer. Natural videos are visually evaluated by paying particular attention to artifacts such as quantization, hue shift, and face-rendering artifacts among others. The more severe and the more frequent the artifact, the higher the point deduction from the score. The main artifacts and corresponding point loss are listed below
Main video artifacts penalties
