We put the MSI Prestige 14 Flip AI+ 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
MSI Prestige 14 Flip AI+
75
camera
49
Microsoft Surface Pro 13-inch
Best: Microsoft Surface Pro 13-inch (93)
15
Lenovo ThinkPad X9 Aura
Best: Lenovo ThinkPad X9 Aura (56)
79
Microsoft Surface Laptop 13.8-inch
Best: Microsoft Surface Laptop 13.8-inch (84)
61
Apple MacBook Pro 14" (M5; 2025)
Best: Apple MacBook Pro 14" (M5; 2025) (85)
66
Microsoft Surface Laptop 13.8-inch
Best: Microsoft Surface Laptop 13.8-inch (146)
100
Microsoft Surface Laptop 13.8-inch
Best: Microsoft Surface Laptop 13.8-inch (146)
Pros
- Acceptable face exposure in typical video conferencing conditions
- Good detail levels in bright lighting conditions
Cons
- Underexposed video in low-light conditions
- Inaccurate color rendering in home and family video scenarios
- Limited detail preservation for darker skin tones and for fair to light skin tones in low-light conditions
In our comprehensive evaluation, the MSI Prestige 14 Flip AI+ delivers generally acceptable performance in video conferencing scenarios, particularly in well-lit environments where face exposure remains satisfactory. One of its key strengths is its ability to provide a high level of detail under bright lighting conditions, ensuring that subjects remain reasonably clear and well-defined (as shown in the visuals below).
However, the performance becomes less convincing in low-light conditions, where video exposure is insufficient, resulting in darker and less clearly rendered faces. Color accuracy is also a weakness, particularly for home and family video use cases, where colors may appear less natural. Additionally, detail rendering is limited in certain conditions, with a noticeable loss of detail for darker skin tones overall, as well as for fair to light skin tones in low-light environments.
Overall, the camera provides acceptable face exposure and good detail levels in bright lighting conditions, making it suitable for video conferencing in favorable environments. However, under more challenging lighting conditions, low exposure, inaccurate color rendering, and reduced detail levels particularly across different skin tones limit its overall performance.
Microsoft Surface Laptop 13.8” (8th Gen)
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
75
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.
Camera texture acutance on Deadleaves with illuminance levels (Eugene)
This graph shows the evolution of texture acutance with the level of lux measured on a Deadleaves chart.
Camera texture acutance on Deadleaves with illuminance levels (Eugene)
This graph shows the evolution of texture acutance with the level of lux measured on a Deadleaves chart.
Camera texture acutance on Deadleaves with illuminance levels (Eugene)
This graph shows the evolution of texture acutance with the level of lux measured on a Deadleaves chart.
Camera texture acutance on Deadleaves with illuminance levels (Eugene)
This graph shows the evolution of texture acutance with the level of lux measured on a Deadleaves chart.
Camera texture acutance on Deadleaves with illuminance levels (Diana)
This graph shows the evolution of texture acutance with the level of lux measured on a Deadleaves chart.
Camera texture acutance on Deadleaves with illuminance levels (Diana)
This graph shows the evolution of texture acutance with the level of lux measured on a Deadleaves chart.
Camera texture acutance on Deadleaves with illuminance levels (Diana)
This graph shows the evolution of texture acutance with the level of lux measured on a Deadleaves chart.
Camera texture acutance on Deadleaves with illuminance levels (Diana)
This graph shows the evolution of texture acutance with the level of lux measured on a Deadleaves chart.
Camera visual noise evolution with illuminance levels (Eugene)
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.
Camera visual noise evolution with illuminance levels (Eugene)
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.
Camera visual noise evolution with illuminance levels (Eugene)
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.
Camera visual noise evolution with illuminance levels (Eugene)
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.
Camera visual noise evolution with illuminance levels (Diana)
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.
Camera visual noise evolution with illuminance levels (Diana)
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.
Camera visual noise evolution with illuminance levels (Diana)
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.
Camera visual noise evolution with illuminance levels (Diana)
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 in HDR conditions (Eugene)
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 (Eugene)
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 (Eugene)
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 (Eugene)
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 (Diana)
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 (Diana)
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 (Diana)
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 (Diana)
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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