We put the Apple iPhone 16 through our rigorous SBMARK Camera test suite to measure its performance in photo, video and zoom quality 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
Key Camera Specifications:
- Main: 48MP lens, 26mm equivalent f/1.6 aperture, Dual Pixel PDAF, sensor-shift OIS
- Ultra-wide: 12MP sensor, 13mm equivalent, f/2.2 aperture lens, 120° field of view, Dual Pixel PDAF
- Chipset A18
Pro
- Pleasant brightness and contrast with images displayed on the HDR display
- Nice skin tones and nice colors for photos and videos
- High levels of detail in bright light and when shooting indoors
- Fast and generally accurate autofocus
- Smooth zoom in preview
- Vivid brightness and contrast with videos viewed on the HDR display
- Video noise is generally well under control
- Pretty effective video stabilization
Against
- Limited dynamic range can cause highlights in photos and videos to be clipped
- Flare, hue shift artifacts, and ringing in photos
- Limited long-range telephoto zoom capabilities
- Loss of detail in videos, especially in low light conditions
- Artifacts may be evident in video, including glare, moving textures in low light, and aliasing
- Noise in the shadows of the frame and in low-light images
In SBMARK Camera tests, the Apple iPhone 16 delivered very good performance for its class. With the exception of the improved autofocus and faster ultra-wide camera lens, the new device uses nearly identical camera hardware to its predecessor, but software changes have led to performance improvements in several test areas. In our evaluations, the camera captured pleasing stills and video with excellent exposure, good contrast, and pleasing skin tones. The video stabilization system kept things smooth and stable when recording moving images. The downside is that the lack of a dedicated telephoto lens meant that images captured at medium- and long-range tele settings lacked detail and texture.
Test summary
About SBMARK Camera Tests: SBMARK camera evaluations take place in laboratories and real-world situations using a wide variety of subjects. Scores are based on objective tests whose results are calculated directly by measurement software in our laboratory setups, and on perceptual tests where a sophisticated set of metrics allows a panel of imaging experts to compare aspects of image quality images that require human judgment. Testing a smartphone involves a team of engineers and technicians for about a week. Photo, zoom and video quality are evaluated separately and then combined into an overall score for comparing cameras on different devices. For more information on the SBMARK camera protocol, click here. More details on smartphone camera scores 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 camera scores
This graph compares SBMARK photo, zoom, and video scores between the tested device and the references. 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 database of tested devices.
Photo
149
Huawei Pura 70 Ultra
Huawei Pura 70 Ultra
About SBMARK Camera Photo Tests
For scoring and analysis, SBMARK engineers capture and evaluate more than 2,600 test images in both controlled laboratory environments and natural outdoor, indoor, and low-light scenes, using the camera’s default settings. The photography protocol is designed to take into account key use cases and is based on typical shooting scenarios, such as portrait, family and landscape photography. 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 2,300K to 6,500K.
In our tests, the overall still image performance of the Apple iPhone 16 was quite close to that of its predecessor iPhone 15 but, thanks to the processing changes, improvements were seen in some areas. Apple’s HDR processing allowed for a wide dynamic range and good subject exposure. The iPhone 16 provided better color management than its predecessor in all test conditions and slightly improved color rendition in daylight and low-light conditions. Autofocus is unchanged, with reliable focus but a slightly shallower depth of field, which could lead to out-of-focus background subjects in group shots. In our lab tests, the iPhone 16 provided slightly better noise handling in low-light conditions than its predecessor, but textures fell slightly short. On the new model, we also observed some slight exposure instabilities when shooting in bright light or indoors.
Apple iPhone 16 vs Premium Photo Scores
Photography tests analyze image quality attributes such as exposure, color, texture and noise under various lighting conditions. Autofocus performance and the presence of artifacts are also evaluated on all images captured under controlled laboratory conditions and in real-life images. All of these attributes have a significant impact on the final quality of images captured with the tested device and can help understand the camera’s key strengths and weaknesses.
Exposure
124
Huawei Pura 70 Ultra
Huawei Pura 70 Ultra
Color
129
Apple iPhone 16 Pro
Apple iPhone 16 Pro
Exposure and color are the key attributes for technically good images. For exposure, the main attribute evaluated is the brightness of the main subject across various use cases such as landscape, portrait or still life. 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 multiple images of the same scene.
Regarding color, the image quality attributes analyzed are skin tone rendering, white balance, color shading and repeatability. Regarding color and skin tone rendering, we penalize unnatural colors but respect the manufacturer’s choice of color signature.


Apple iPhone 15 – Accurate target exposure, warm white balance with beautiful colors

Google Pixel 9 – Precise target exposure, warm white balance with pleasant colors
Auto focus
100
Huawei Pura 70 Ultra
Huawei Pura 70 Ultra
Autofocus tests focus on focus accuracy, focus repeatability, shutter lag, and depth of field. Shutter delay is the difference between when the user presses the capture button and when the image is actually taken. It includes focusing speed and the device’s ability to capture images at the right time, the so-called “zero shutter lag” capability. While a shallow depth of field can be nice for single-subject portraits or close-ups, it can also pose a problem in some specific conditions such as group portraits; Both situations are tested. Focus accuracy is also evaluated in all real-world images taken, from infinity to close-up objects and low-light to outdoor conditions.
Autofocus irregularity and speed: 1000Lux Δ0EV portable daylight
Structure
109
Apple iPhone 15 Pro
Apple iPhone 15 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 in the light and dark areas of the image. 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.
SBMARK CHART (DMC) Detail Retention Score vs. Lux Levels for Tripod and Handheld Conditions
This graph shows the evolution of the DMC detail retention score with lux level, for two retention conditions. The DMC Detail Retention Score is derived from an AI-based metric trained to evaluate the performance of texture and detail on a selection of crops from our SBMARK chart.
Noise
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Huawei Pura 70 Ultra
Huawei Pura 70 Ultra
Noise tests analyze various noise attributes such as intensity, chromaticity, grain, texture on real-life images and on graph images taken in the laboratory. For natural images, particular attention is paid to noise on faces, landscapes, but also on dark areas and high dynamic range conditions. Noise on moving objects is also evaluated on natural images. 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 dead leaf graph and 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 AFHDR configuration. SBMARK visual noise measurement is derived from the ISO15739 standard.
Artifacts
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XiaomiRedmi 12 5G
XiaomiRedmi 12 5G
Artifact evaluation examines lens shading, chromatic aberrations, geometric distortion, ringing edges, halos, ghosting, quantization, unexpected color tone changes, among other types of possible unnatural effects on the photos. 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
80
Huawei Pura 70 Ultra
Huawei Pura 70 Ultra
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 DLSR 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 – Accurate segmentation, natural bokeh effect
Preview
84
Apple iPhone 16 Pro
Apple iPhone 16 Pro
Preview tests analyze the quality of the camera app’s image preview, with a focus on the difference between capture and preview, particularly regarding dynamic range and the application of bokeh. The smoothness of exposure, color and focus adaptation when switching from the minimum to the maximum available zoom factor is also evaluated. The preview frame rate is measured using the LED universal timer.

Apple iPhone 16 – Preview – Close enough to the shot, even in difficult conditions

Apple iPhone 16 – Capture
Zoom
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Huawei Pura 70 Ultra
Huawei Pura 70 Ultra
Learn about SBMARK camera zoom tests
SBMARK engineers capture and evaluate more than 400 test images in controlled laboratory environments and in natural scenes outdoors, indoors, and in low-light conditions, using default camera settings and pinch zoom at various zoom factors from ultra wide zoom to long range zoom. The evaluation is performed by visually examining the images Cons a reference of natural scenes and performing objective measurements of map images captured in the laboratory under different conditions from 20 to 1000 lux and color temperatures from 2300K to 6500K.
Unlike the Pro version, the Apple iPhone 16 does not come with a dedicated telephoto lens. As expected, image results at medium and long-range tele settings were therefore rather limited in terms of texture and detail. That said, long-range texture was slightly better than on the iPhone 15 predecessor. Additionally, slight autofocus updates and a faster lens on the ultra-wide camera led to some texture improvements in ultra-wide shots. Overall, however, ultra-wide performance is similar to its predecessor.
In contrast to the Pro version, the iPhone 16 does not have a tele module, only the main module and a slightly updated ultrawide.
Apple iPhone 16 Zoom Scores vs. Premium
This graph illustrates the relative scores for the different zoom ranges evaluated. The abscissa is expressed in focal length equivalent to 35 mm. Zoomed scores appear on the right and zoomed scores appear on the left.
Wide
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Huawei Pura 70 Ultra
Huawei Pura 70 Ultra
These tests analyze the performance of the ultra-wide camera at different focal lengths from 12mm to 20mm. All image quality attributes are evaluated, with particular attention to artifacts such as chromatic aberrations, lens softness and distortion. The images below are an excerpt of the tested scenes.

Apple iPhone 16 – Neutral colors, good exposure and detail

Apple iPhone 15 – Saturated colors, good exposure and detail

Google Pixel 9 – Neutral colors, darker exposure and good details
Tele
83
Xiaomi 14Ultra
Xiaomi 14Ultra
All image quality attributes are evaluated at focal lengths between approximately 40mm and 300mm, with particular attention to texture and detail. The score is derived from a series of objective measurements in the laboratory and perceptual analysis of real-life images.
SBMARK CHART (DMC) detail retention score by focal length
SBMARK CHART (DMC) detail retention score by focal length
This graph shows the evolution of the DMC detail retention score versus the full-frame equivalent focal length for different lighting conditions. The x-axis represents the equivalent focal length measured for each corresponding shooting distance, and the y-axis represents the maximum detail retention metric score – a higher value means better quality. The large dots correspond to the zoom ratio available in the camera application user interface.
SBMARK CHART (DMC) detail retention score by focal length
This graph shows the evolution of the DMC detail retention score versus the full-frame equivalent focal length for different lighting conditions. The x-axis represents the equivalent focal length measured for each corresponding shooting distance, and the y-axis represents the maximum detail retention metric score – a higher value means better quality. The large dots correspond to the zoom ratio available in the camera application user interface.
SBMARK CHART (DMC) detail retention score by focal length
This graph shows the evolution of the DMC detail retention score versus the full-frame equivalent focal length for different lighting conditions. The x-axis represents the equivalent focal length measured for each corresponding shooting distance, and the y-axis represents the maximum detail retention metric score – a higher value means better quality. The large dots correspond to the zoom ratio available in the camera application user interface.
Video
154
Apple iPhone 16 Pro
Apple iPhone 16 Pro
About SBMARK Camera Video Tests
SBMARK engineers capture and evaluate more than 2.5 hours of video in controlled laboratory environments and natural low-light scenes, indoors and outdoors, using default 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.
Video performance was excellent for this class of device. As with still images, overall video quality was quite similar to its predecessor. Our testers noticed some improvements, particularly in the color category, with better white balance. The new model also offers better video texture than last year’s device, while noise may be a little more intrusive on the iPhone 16.
Apple iPhone 16 Video Scores vs. Premium
Exposure
114
Apple iPhone 15 Pro
Apple iPhone 15 Pro
Exposure tests evaluate the brightness of the main subject and the 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 color rendering, skin tone rendering, white balance, color shading, white balance stability and its adaptation when the light changes.
Apple iPhone 16 – Accurate exposure, beautiful colors
Apple iPhone 15 – Accurate exposure, beautiful colors
Google Pixel 9 – Accurate exposure, beautiful colors
Structure
108
Oppo Find X6 Pro
Oppo Find X6 Pro
Texture tests analyze the level of detail and texture of real videos and graphics videos recorded in the lab. Natural video footage is assessed visually, paying particular attention to the level of detail in bright and dark areas. Objective measurements are performed on chart images taken under various conditions from 1 to 1000 lux. The cards used are SBMARK (DMC) card and Dead Leaves card.
SBMARK CHART (DMC) Video detail retention score versus lux levels
This graph shows the evolution of the DMC detail retention video score with the lux level in the video. The DMC Detail Retention Score is derived from an AI-based metric trained to evaluate the performance of texture and detail on a selection of crops from our SBMARK chart.
Noise
117
Apple iPhone 16 Pro
Apple iPhone 16 Pro
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 in dark areas and high dynamic range conditions. 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.
Stabilization
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Apple iPhone 16 Pro
Apple iPhone 16 Pro
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 residual motion, smoothness, yellow artifacts, and residual motion blur in walking and running use cases under various lighting conditions. The video below is an excerpt of one of the scenes tested.
Apple iPhone 16 – Smooth stabilization when walking while recording
Apple iPhone 15 – Smooth stabilization when walking while recording
Google Pixel 9 – Effective stabilization when walking while recording
Artifacts
83
Xiaomi 12S Ultra
Xiaomi 12S Ultra
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 paying particular attention to artifacts such as aliasing, quantization, blocking, and hue shifting, 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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