We put the Apple iPhone 16 Pro Max through our rigorous SBMARK Selfie test suite to measure its photo and video performance from an end-user perspective. This article analyzes the behavior of the device in a series of tests and several common use cases and aims to highlight the most important results of our tests with an excerpt of the acquired data.
Overview
Front camera main specifications:
- 12 MP sensor
- Lens with f/1.9 aperture
- Auto focus
- 4K video at 24/25/30/60 fps, 1080p at 25/30/60/120 fps (4K at 30 fps tested)
Pro
- Accurate exposure and wide dynamic range, high contrast on HDR screens.
- Reliable autofocus and wide depth of field
- High levels of detail, in both photo and video modes
- Simulated large aperture and natural bokeh effect in portrait mode
Against
- Noise in photos and videos
- White balance projects in photos
- Occasional differences in sharpness between video frames when walking while recording
The Apple iPhone 16 Pro Max performed exceptionally well in the SBMARK Selfie tests, securing the top spot in our ranking, despite using very similar front camera hardware to last year’s model and only minor improvements on the software side.
In our tests, Apple’s HEIC image files with HDR data embedded looked stunning when viewed on a dedicated HDR display. Image and video results were stunning in both the Photos app on macOS Sonoma on an XDR display and the Photos app on the iPhone 15 Pro Max display, rendering brighter and more vivid than ever. However, users of displays, devices, or apps that don’t support Apple’s HDR photo format will only see JPG images without the HDR effect.
Apple iPhone 16 Pro Max vs Ultra-Premium Selfie Scores
This chart compares overall SBMARK Selfie scores for photos and videos between tested and reference devices. The average and maximum scores of the price range are also indicated. The average and maximum scores for each price segment are calculated based on the SBMARK device database.
Test summary
About SBMARK selfie tests: For scoring and analysis, SBMARK engineers capture and evaluate more than 1,500 test images in both controlled laboratory environments and natural outdoor, indoor, and low-light scenes, using default front camera settings. The photography protocol is designed to take user needs into account and is based on typical shooting scenarios, such as close-ups and group selfies. Evaluation is performed by visually examining images Cons a natural scene reference and performing objective measurements on laboratory-captured graph images under varying lighting conditions from 1 to 1,000+ lux and color temperatures from 2,300 K to 6,500 K. Learn more information about the SBMARK Selfie test protocol, click here. More details on how we rate smartphone cameras can be found here. The following section compiles key elements of SBMARK’s comprehensive testing and analysis. Full performance evaluations are available upon request. Please contact us to find out how to receive a full report.
Apple iPhone 16 Pro Max Photo Scores vs. Ultra-Premium
In our tests, the Apple iPhone 16 Pro Max delivered excellent selfie images, with an overall appearance close to its predecessor 15 Pro Max. The improvements were especially noticeable in terms of texture and noise.
Like its predecessor, the new model performed particularly well in terms of exposure, capturing a wide dynamic range, offering excellent subject exposure and providing high contrast levels with images viewed on HDR displays. Overall exposure results were even slightly improved over the 15 Pro Max. Color was on par with the best in the category, although the Google Pixel 9 Pro XL delivered better white balance and skin tones in some outdoor scenes. ‘open.
The level of detail captured was quite similar to last year’s device, with nice facial detail at all shooting distances, thanks to the front camera’s excellent autofocus. The lower noise levels were a significant improvement over the 15 Pro Max, but slight luminance noise remained evident in the background of the image. The bokeh effect, which provides the strong blur of a simulated large aperture, was another highlight of the iPhone 16 Pro Max’s front-facing camera photo mode.
Apple iPhone 16 Pro Max –
Excellent highlight protection and subject exposure, high contrast on the HDR display
Honor Magic6 Pro – Excellent highlight protection, good subject exposure
Color
103
Google Pixel 9 ProXL
Google Pixel 9 ProXL
Exposure and color are the key attributes for technically good images. For exposure, the main attribute evaluated is the brightness of faces under various use cases and lighting conditions. Other factors evaluated are contrast and dynamic range, e.g. the ability to make details visible 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.
Regarding color, the image quality attributes analyzed are skin tone rendering, white balance, color shading and repeatability.
Apple 16 Pro Max – Slightly cool color domination on the subject
Google Pixel 9 Pro XL – Excellent white balance
and skin tones
Honor Magic6 Pro – Slightly cool color cast
on topic
Focus
103
Honor Magic6 Pro
Honor Magic6 Pro
Autofocus tests evaluate the precision of focus on the subject’s face, the repeatability of accurate focus, and the depth of field. While a shallow depth of field can be nice for a single-subject selfie or close-up shot, it can be problematic in specific conditions like group selfies; both situations are tested. Focus accuracy is also evaluated in all real images taken, from 30cm to 150cm, and in low-light or outdoor conditions.
Apple iPhone 16 Pro Max – Accurate focus, good details on all subjects
Google Pixel 9 Pro XL – Accurate focus, good details on all subjects
Honor Magic6 Pro – Accurate focus, even better details on all subjects
Structure
77
Asus ZenFone 7 Pro
Asus ZenFone 7 Pro
Texture tests analyze the level of detail and texture of subjects in images taken in the laboratory and in real-life scenarios. For natural shots, special attention is paid to the level of detail of facial features, such as the eyes. Objective measurements are performed on map images taken under various lighting conditions from 1 to 1000 lux and different types of dynamic range conditions. The papers used are the proprietary SBMARK (DMC) paper and the Dead Leaves paper.
Evolution of texture sharpness with illuminance level
Noise
67
Huawei Mate 50 Pro
Huawei Mate 50 Pro
Noise tests analyze various noise attributes such as intensity, chromaticity, grain and texture on real images and on graph images taken in the laboratory. For natural images, particular attention is paid to noise on faces, but also to dark areas and high dynamic range conditions. Objective measurements are performed on graph images taken under various conditions from 1 to 1000 lux and different types of dynamic range conditions. The graph used is the SBMARK Dead Leaves graph and the standardized measurement such as visual noise derived from ISO 15739.
Evolution of visual noise with illuminance levels under handheld conditions
This graph shows the evolution of the visual noise metric with lux level in handheld conditions. The visual noise metric is the average of the visual noise measurement across all areas of the Dead Leaves graph in the Close-up Dead Leaves setting. SBMARK visual noise measurement is derived from the ISO15739 standard.
Artifact evaluation examines lens shading, chromatic aberrations, distortion measurements on the Dot and MTF graph, and sound measurements on the SFR graph in the lab. Particular attention is paid to ghosting, quantization, halos and tone changes on the face, among others. The more severe and frequent the artifact, the greater the point deduction from the score. The main artifacts observed and the corresponding point loss are listed below.
Major penalties for photography artifacts
Bokeh is tested in a dedicated mode, usually portrait or aperture mode, and analyzed by visually inspecting all images captured in the laboratory and in natural conditions. The goal is to reproduce a portrait photograph comparable to one taken with a DSLR and a wide aperture. The main image quality attributes that were paid attention to are depth estimation, artifacts, blur gradient, and the shape of the bokeh blur spotlights. The quality attributes of the portrait image (exposure, color, texture) are also taken into account.
Apple iPhone 16 Pro Max: Simulated large aperture and accurate depth estimation
Google Pixel 9 Pro XL – Simulated narrower aperture, artifacts in hair and around clothing
Video
155
Apple iPhone 15 Pro
Apple iPhone 15 Pro
About SBMARK selfie video tests
SBMARK engineers capture and evaluate more than 2 hours of video in controlled laboratory environments and natural low-light scenes, indoors and outdoors, using default front camera settings. The evaluation consists of visual inspection of natural videos taken under various conditions and performing objective measurements on videos of graphs recorded in the laboratory under different conditions from 1 to 1000+ lux and color temperatures from 2,300 K to 6,500 K.
Apple iPhone 16 Pro Max Video Scores vs. Ultra-Premium
The Apple iPhone 16 Pro Max was a standout device for recording video from the front camera, excelling in the exposure, white balance, and stabilization test categories. These strengths have resulted in excellent overall selfie video quality and a top ranking in the SBMARK Selfie Video ranking.
Compared to the predecessor iPhone 15 Pro Max, noise reduction has been improved. That said, its performance in video mode wasn’t flawless, and our testers observed some of the same issues we already saw on last year’s model, including very slight clipping of highlights in HDR scenes and slight inconsistencies in skin tone in low light conditions. Video stabilization was very effective overall, but there may be occasional variations in sharpness between frames and slight camera shake when moving during recording.
Color
89
Apple iPhone 15 Pro
Apple iPhone 15 Pro
Exposure tests evaluate facial brightness and dynamic range, e.g. the ability to make details visible in both bright and dark areas of the image. The stability and temporal adaptation of the exposure are also analyzed. Image quality color analysis examines skin tone rendering, white balance, color shading, white balance stability and how it adapts when the light changes.
Apple iPhone 16 Pro Max – Precise facial exposure, pleasant skin tones, even Cons backlight
Google Pixel 9 Pro XL – Accurate face exposure, skin tones slightly too dark, skin tones slightly orange with backlight
Honor Magic 6 Pro – Facial exposure is accurate, skin tones are slightly too deep, slightly orange when backlit
Structure
83
Asus Zenfone 6
Asus Zenfone 6
Texture tests analyze the level of detail and texture of real videos and graphics videos recorded in the laboratory. Natural video footage is evaluated visually, with particular attention to the level of detail of facial features. Objective measurements are performed on chart images taken under various conditions from 1 to 1000 lux. The chart used is the Dead Leaves chart.
Evolution of texture sharpness with illuminance level
This graph shows the evolution of texture sharpness with lux level for two holding conditions. Texture sharpness is measured on the Dead Leaves graph in the Close-up Dead Leaves setting.
Noise
74
Xiaomi Mi 11 Ultra
Xiaomi Mi 11 Ultra
Noise tests analyze various noise attributes such as intensity, chromaticity, grain, structure, temporal aspects on real video recordings and on videos of graphs taken in the laboratory. Natural videos are evaluated visually, with particular attention to noise on faces. Objective measurements are performed on graph videos recorded under various conditions from 1 to 1000 lux. The graph used is the SBMARK visual noise graph.
Evolution of spatial visual noise with illuminance level
Temporal evolution of visual noise with illuminance level
This graph shows the evolution of temporal visual noise with lux level. Temporal visual noise is measured on the visual noise graph in the video noise setup.
The stabilization rating checks the device’s ability to stabilize footage thanks to software or hardware technologies such as OIS, EIS or any other means. The evaluation examines overall residual motion on the face and background, smoothness, and yellow artifacts, during walking and panning use cases under various lighting conditions. The video below is an excerpt of one of the scenes tested.
Apple iPhone 16 Pro Max – Effective overall stabilization, slight differences in sharpness between frames and camera shake
Google Pixel 9 Pro XL – Overall effective stabilization, very slight differences in sharpness between frames and camera movement
Honor Magic6 Pro – Effective overall stabilization, slight differences in sharpness between frames and camera movement
Artifacts
86
Apple iPhone 12 mini
Apple iPhone 12 mini
Artifacts are evaluated with MTF and ringing measurements on the SFR graph 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 frequent the artifact, the greater the deduction of points from the score. The main artifacts and the corresponding point loss are listed below
Top penalties for video artifacts
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