We put the Huawei MateBook X Pro 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
Huawei MateBook X Pro 2024
94
camera
76
Apple MacBook Pro 14" (M3 Pro, 2023)
Best: Apple MacBook Pro 14" (M3 Pro, 2023) (93)
37
Microsoft Surface Pro 11th edition Copilot+PC
Best: Microsoft Surface Pro 11th edition Copilot+PC (54)
43
Apple MacBook Pro 14" (M3 Pro, 2023)
Best: Apple MacBook Pro 14" (M3 Pro, 2023) (76)
78
Apple MacBook Pro 14" (M2 Pro, 2023)
Best: Apple MacBook Pro 14" (M2 Pro, 2023) (83)
Pros
- Generally good face exposure
- Subjects are always in focus
- Good level of details in bright light conditions
Cons
- Colors and skin tones are desaturated
- Exposure instabilities are visible when the subject is in motion
- Noise is visible and details are lost in low-light conditions
- Dynamic range is slightly low on contrasted scenes
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 in the form of reports are available upon request. Do not hesitate to contact us.
Camera
94
Huawei MateBook X Pro 2024
135
Apple MacBook Pro 14" (M3 Pro, 2023)
Apple MacBook Pro 14" (M3 Pro, 2023)
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.
The Huawei MateBook X Pro 2024 generally offers good face exposure, while keeping the subject in focus in most conditions. Dynamic range is slightly limited, leading to some loss of details in bright or dark parts, even with low contrasted scenes. Additionally, when the subject is moving, some exposure instabilities can be visible. Color rendering and skin tones, however, are often desaturated. In bright conditions, the texture-noise tradeoff is good, with a high level of details. But in low-light conditions, noise can be visible.
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.
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