Redmi G Pro 27U vs Redmi G24
Redmi G24 — Pick the Redmi G24 — it leads these groups: Ergonomics 1
Tap a group name to see the proof · The scoring method is public
The short answer
Redmi G24 wins this comparison with a score of 58/100, ahead of Redmi G Pro 27U (57).
The main differences: Screen size (27 in vs 23.8 in) · Resolution (3840x2160 vs 1920x1080) · Max refresh rate (160 Hz vs 180 Hz).
Scores are computed from 5 public spec attributes; missing values stay marked unknown in tables and are imputed at the category median, never passed off as measured.
At a glance
0–100 per group, normalized within the category · Tap a group for details
| Redmi G Pro 27U | Redmi G24 | |
|---|---|---|
| Display | 39 | 38 |
| Ergonomics | 88 | 90 |
How to choose
Pick the Redmi G Pro 27U if you care about…
- Screen size 27 in +3.2 in vs 23.8 in
Pick the Redmi G24 if you care about…
- Max refresh rate 180 Hz +20 Hz vs 160 Hz
- Weight (with stand) 2700 g +2000 g vs 4700 g
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Where they differ
4 · Only rows that actually differ, with a verdict per row
| Redmi G Pro 27U | Redmi G24 | Where they differ | |
|---|---|---|---|
| Screen size | 27 in | 23.8 in | Redmi G Pro 27U |
| Resolution | 3840x2160 | 1920x1080 | Depends |
| Max refresh rate | 160 Hz | 180 Hz | Redmi G24 |
| Weight (with stand) | 4700 g | 2700 g | Redmi G24 |
The record
Grouped and collapsible · Tap a group to fold
Display4▾
| Redmi G Pro 27U | Redmi G24 | |
|---|---|---|
| Screen size | 27 in | 23.8 in |
| Resolution | 3840x2160 | 1920x1080 |
| Max refresh rate | 160 Hz | 180 Hz |
| Panel type | Fast-IPS | Fast-IPS |
Ergonomics1▾
| Redmi G Pro 27U | Redmi G24 | |
|---|---|---|
| Weight (with stand) | 4700 g | 2700 g |
Data sources: GSMArena
FAQ
Which is better, Redmi G Pro 27U or Redmi G24?
Redmi G24 edges ahead 58 to 57 and leads in Ergonomics. Choose Redmi G Pro 27U instead if Screen size matters more to you.
What are the main differences?
The main differences: Screen size (27 in vs 23.8 in) · Resolution (3840x2160 vs 1920x1080) · Max refresh rate (160 Hz vs 180 Hz).
How are the scores calculated?
We normalize 5 public spec attributes within the category and weight them by group into a 0–100 score; missing values are inherited from spec-identical twins or imputed at the category median, so a sparse spec sheet never earns an advantage. The methodology is public.