We put the Apple Macbook Neo 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
Apple Macbook Neo
98
camera
69
Microsoft Surface Pro 13-inch
Best: Microsoft Surface Pro 13-inch (93)
16
Lenovo ThinkPad X9 Aura
Best: Lenovo ThinkPad X9 Aura (56)
80
Microsoft Surface Laptop 13.8-inch
Best: Microsoft Surface Laptop 13.8-inch (84)
67
Apple MacBook Pro 14" (M5; 2025)
Best: Apple MacBook Pro 14" (M5; 2025) (85)
70
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
- Good skin tone rendering in indoor and low-light conditions
- Good HDR performance in indoor conditions
- Accurate face exposure across indoor and low-light conditions
- Barely visible noise in indoor conditions
In our evaluation of the Apple MacBook Neo, the camera delivers a generally strong performance in indoor and low-light conditions, particularly in terms of skin tone rendering, face exposure and HDR performance.
One of the key aspects delivered by the MacBook Neo is its natural skin tone rendering in indoor and low-light conditions. Skin tones remain generally pleasant and well rendered, contributing to a natural appearance during video conferencing. The camera also provides good HDR capabilities in indoor conditions, allowing it to maintain a reasonable balance between brighter and darker areas of the scene.
Face exposure remains accurate from indoor to low-light conditions, ensuring that subjects remain properly visible even when the available light decreases. Noise is also barely visible in indoor conditions, resulting in a relatively clean image when the camera is used in typical video conferencing environments. However, some limitations become noticeable in more challenging conditions. Clipping is visible in low-light scenes, resulting in a loss of detail in brighter areas. Texture rendering is also relatively low on portraits, with fine facial details not being fully preserved. Slight instabilities can additionally be observed in color rendering in indoor conditions, resulting in occasional variations in the overall appearance of the image.
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
98
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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