We put the Microsoft Surface Pro 13-inch through our rigorous DXOMARK Laptop test suite to measure its performance in sound, camera and display. In this review, we will break down how it fared in a variety of tests and several common use cases.
Overview
Scoring
Use-case and feature subscores included in the calculations of the global score
Microsoft Surface Pro 13 inch
144
camera
93
Microsoft Surface Pro 13-inch
40
Lenovo ThinkPad X9 Aura
Best: Lenovo ThinkPad X9 Aura (56)
82
Microsoft Surface Laptop 13.8-inch
Best: Microsoft Surface Laptop 13.8-inch (84)
76
Apple MacBook Pro 14″ (M5; 2025)
Best: Apple MacBook Pro 14″ (M5; 2025) (85)
Pros
- Accurate target exposure in most conditions
- Extended dynamic range in indoor conditions
- Generally accurate white balance with pleasant color rendering
- Low noise levels in bright conditions
- Depth of field well adapted to videoconferencing use cases
Cons
- Slightly limited detail with occasional unnatural detail rendering
- Visible noise in low-light conditions and during motion
- Occasional artifacts, including anamorphosis and quantization
Test summary
About DXOMARK Laptop tests: For scoring and analysis in our laptop reviews, DXOMARK engineers perform a variety of objective tests and undertake more than 20 hours of perceptual evaluations under controlled lab conditions and real-life scenarios. (For more details about the Laptop protocol, click here.)
The following section gathers key elements of our exhaustive tests and analyses performed in DXOMARK laboratories. Detailed performance evaluations under the form of reports are available upon request. Do not hesitate to contact us.
Camera
144
Microsoft Surface Pro 13 inch
146
Microsoft Surface Laptop 13.8-inch
Microsoft Surface Laptop 13.8-inch
About DXOMARK Camera Laptop tests
DXOMARK evaluates the image quality of the built in camera during video calls, whether with a single person or with multiple people, in a variety of lighting conditions. Our camera evaluation particularly assesses the ability of the built-in camera to clearly render human faces during video calls. Other intrinsic camera quality aspects are also evaluated, like color reproduction, texture and noise, as well as artefacts.
In our comprehensive evaluation of laptop cameras, the Microsoft Surface Pro 13’’ (2-in-1) secures the second position in our ranking, ahead of the Apple MacBook Pro 14’’ (M4, 2024). The device delivers a highly competitive camera performance, distinguished by accurate exposure, extended dynamic range, pleasant color rendering, and an imaging pipeline that is particularly well suited to modern video conferencing use cases.
One of the main strengths of the Microsoft Surface Pro 13’’ (2-in-1) is its accurate target exposure across a wide variety of lighting conditions. The camera consistently produces well-balanced images while maintaining an extended dynamic range capable of preserving details in both highlights and shadows. This advantage is especially apparent in backlit scenes, where the Surface Pro 13’’ manages to keep faces properly exposed without excessively sacrificing too much background detail. In comparison, the MacBook Pro 14’’ (M4, 2024) often favors highlight retention, leading to slightly underexposed subject in demanding conditions.
Color rendering is another area where the Microsoft device demonstrates excellent performance. White balance is generally accurate and neutral, producing natural-looking skin tones and pleasant colors in bright environments. The Surface Pro 13’’ also achieves stronger objective color measurements than the MacBook Pro 14’’ (M4, 2024), whose rendering tends to be noticeably warmer with occasional orange tones. As a result, images captured by the Surface Pro often appear more neutral and faithful to the original scene.
Noise performance remains well controlled in most situations. In bright conditions, the camera produces clean images with limited visible noise. The depth of field is also particularly well adapted to video conferencing scenarios, ensuring that subjects remain sharply rendered while maintaining sufficient focus coverage for group calls and varying shooting distances. In terms of texture and noise, the Surface Pro 13’’ performs similarly to the MacBook Pro 14’’ (M4, 2024), with both devices offering a good level of detail and low visible noise under favorable lighting conditions.
The Microsoft Surface Pro 13’’ is not without shortcomings, however. The level of captured detail is slightly limited compared to the very best devices in our ranking, and texture rendering can occasionally appear somewhat unnatural especially in lowlight conditions. In more challenging situations, such as low-light environments or scenes involving motion, noise may become more noticeable and affect image clarity. Certain artifacts, including anamorphosis and quantization, can also be observed in specific conditions.
Nevertheless, the Microsoft Surface Pro 13’’ (2-in-1) delivers a remarkably balanced camera experience that combines accurate exposure, wide dynamic range, natural color reproduction, and effective noise control. Its superior handling of backlit scenes and more neutral color rendering allow it to secure the second position in our ranking, making it one of the strongest performers currently available for video conferencing use case.
The following chart presents the camera subscores for the video call use case:
Camera texture acutance on Deadleaves with illuminance levels
This graph shows the evolution of texture acutance with the level of lux measured on a Deadleaves chart.
The following graphs show the objective measurements performed in our camera labs:
Camera visual noise evolution with illuminance levels
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.
Target exposure on face with illuminance levels
These measurements take place on a setup combining realistic mannequins and a backlit panel simulating high dynamic range conditions. This graph shows the evolution of lightness measured on the forehead of the realistic mannequin with the level of lux, for multiple lighting conditions. The lightness is measured in L*. Delta EV specifies the difference of luminance in stops between the face and the light panel simulating HDR conditions.
Target exposure on face with illuminance levels in HDR conditions
These measurements take place on a setup combining realistic mannequins and a backlit panel simulating high dynamic range conditions. This graph shows the evolution of lightness measured on the forehead of the realistic mannequin with the level of lux, for multiple lighting conditions. The lightness is measured in L*. Delta EV specifies the difference of luminance in stops between the face and the light panel simulating HDR conditions.
Target exposure on face with illuminance levels in HDR conditions
These measurements take place on a setup combining realistic mannequins and a backlit panel simulating high dynamic range conditions. This graph shows the evolution of lightness measured on the forehead of the realistic mannequin with the level of lux, for multiple lighting conditions. The lightness is measured in L*. Delta EV specifies the difference of luminance in stops between the face and the light panel simulating HDR conditions.
