We put the Microsoft Surface Laptop 13.8-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 Laptop 13.8 inch
146
camera
90
Microsoft Surface Pro 13-inch
Best: Microsoft Surface Pro 13-inch (93)
45
Lenovo ThinkPad X9 Aura
Best: Lenovo ThinkPad X9 Aura (56)
84
Microsoft Surface Laptop 13.8-inch
77
Apple MacBook Pro 14″ (M5; 2025)
Best: Apple MacBook Pro 14″ (M5; 2025) (85)
Pros
- Accurate and stable target exposure in most conditions
- Neutral white balance with pleasant color rendering
- Accurate focus with wide depth of field
- Decent level of detail and low noise in bright conditions
Cons
- Occasional loss of fine details, especially in low-light conditions
- Visible temporal noise, particularly during motion
- Occasional artifacts, including ghosting
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.
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 Laptop 13.8’’ achieves the highest score in our ranking with an outstanding result of 146, surpassing the Apple MacBook Pro 14’’ (M4, 2024) and setting a new benchmark for laptop camera performance. The device delivers an very well balanced imaging experience, combining accurate exposure, natural color reproduction, and reliable focus behavior across a wide range of usage scenarios.
One of the key strengths of the Microsoft Surface Laptop 13.8’’ is its ability to provide accurate and stable target exposure in all tested lighting conditions. This advantage is particularly noticeable in challenging backlit scenes, where the device maintains a well-exposed subject while preserving a high level of detail in the background. By comparison, the MacBook Pro 14’’ (M4, 2024) tends to prioritize highlight preservation, occasionally resulting in slightly underexposed faces. The Surface Laptop 13.8’’ therefore achieves a more balanced rendering, making video calls appear more natural and visually pleasing.
Color performance is another area where the device stands out. White balance remains generally neutral, contributing to accurate color reproduction and pleasant skin tones across a variety of environments. Compared to the MacBook Pro 14’’ (M4, 2024), which often exhibits a warmer rendering with a slight orange cast, the Surface Laptop 13.8’’ delivers a more faithful representation of the scene. This results in images that appear more natural and consistent, particularly during extended video conferencing sessions.
The Microsoft Surface Laptop 13.8’’ also benefits from accurate autofocus and a wide depth of field, allowing subjects to remain sharp across a broad range of distances. This characteristic proves particularly useful in collaborative environments or group calls, where focus consistency remains dependable. In bright lighting conditions, the camera captures a decent level of detail while maintaining low noise levels, producing clean and visually appealing footage.
Despite its class-leading performance, some limitations remain. Fine details can occasionally be lost, particularly in low-light environments where texture preservation becomes more challenging. Temporal noise is often visible during motion even in bright conditions and may slightly reduce perceived image quality in dynamic scenes. In addition, artifacts such as ghosting can sometimes be observed, although their impact generally remains limited.
Overall, the Microsoft Surface Laptop 13.8’’ delivers the best camera experience in our ranking. Its combination of excellent exposure management, neutral color rendering, robust focus performance, and strong performance in challenging backlit scenes allows it to outperform the MacBook Pro 14’’ (M4, 2024) and establish itself as the current reference for laptop camera quality.
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.
