Redmi RMMNT27NF vs Redmi RMMNT27NQ
Redmi RMMNT27NQ — Pick the Redmi RMMNT27NQ — it leads these groups: Ergonomics 1
Tap a group name to see the proof · The scoring method is public
The short answer
Redmi RMMNT27NQ wins this comparison with a score of 63/100, ahead of Redmi RMMNT27NF (61).
The main differences: Resolution (1920x1080 vs 2560x1440) · Max refresh rate (75 Hz vs 60 Hz) · Weight (with stand) (4300 g vs 4200 g).
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 RMMNT27NF | Redmi RMMNT27NQ | |
|---|---|---|
| Display | 39 | 46 |
| Ergonomics | 86 | 86 |
How to choose
Pick the Redmi RMMNT27NF if you care about…
- Max refresh rate 75 Hz +15 Hz vs 60 Hz
Pick the Redmi RMMNT27NQ if you care about…
- Weight (with stand) 4200 g +100 g vs 4300 g
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Where they differ
3 · Only rows that actually differ, with a verdict per row
| Redmi RMMNT27NF | Redmi RMMNT27NQ | Where they differ | |
|---|---|---|---|
| Resolution | 1920x1080 | 2560x1440 | Depends |
| Max refresh rate | 75 Hz | 60 Hz | Redmi RMMNT27NF |
| Weight (with stand) | 4300 g | 4200 g | Redmi RMMNT27NQ |
The record
Grouped and collapsible · Tap a group to fold
Display4▾
| Redmi RMMNT27NF | Redmi RMMNT27NQ | |
|---|---|---|
| Screen size | 27 in | 27 in |
| Resolution | 1920x1080 | 2560x1440 |
| Max refresh rate | 75 Hz | 60 Hz |
| Panel type | — | IPS |
Ergonomics1▾
| Redmi RMMNT27NF | Redmi RMMNT27NQ | |
|---|---|---|
| Weight (with stand) | 4300 g | 4200 g |
Data sources: GSMArena
FAQ
Which is better, Redmi RMMNT27NF or Redmi RMMNT27NQ?
Redmi RMMNT27NQ edges ahead 63 to 61 and leads in Ergonomics. Choose Redmi RMMNT27NF instead if Max refresh rate matters more to you.
What are the main differences?
The main differences: Resolution (1920x1080 vs 2560x1440) · Max refresh rate (75 Hz vs 60 Hz) · Weight (with stand) (4300 g vs 4200 g).
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.