Xlite v4 Mini Gaming Mouse vs Xlite v1 Gaming Mouse
The short answer
Xlite v4 Mini Gaming Mouse wins this comparison with a score of 50/100, ahead of Xlite v1 Gaming Mouse (49).
The main differences: Max DPI (32000 DPI vs 26000 DPI) · Weight (54 g vs 52 g) · Buttons (2 vs 5).
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
| Xlite v4 Mini Gaming Mouse | Xlite v1 Gaming Mouse | |
|---|---|---|
| Performance | 69 | 62 |
| Design | 19 | 30 |
| Connect | 68 | 63 |
How to choose
Pick the Xlite v4 Mini Gaming Mouse if you care about…
- Max DPI 32000 DPI +6000 DPI vs 26000 DPI
Pick the Xlite v1 Gaming Mouse if you care about…
- Weight 52 g +2 g vs 54 g
- Buttons 5 +3 vs 2
- Wired ✓ vs —
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Where they differ
4 · Only rows that actually differ, with a verdict per row
| Xlite v4 Mini Gaming Mouse | Xlite v1 Gaming Mouse | Where they differ | |
|---|---|---|---|
| Max DPI | 32000 DPI | 26000 DPI | Xlite v4 Mini Gaming Mouse |
| Weight | 54 g | 52 g | Xlite v1 Gaming Mouse |
| Buttons | 2 | 5 | Xlite v1 Gaming Mouse |
| Wired | — | ✓ | Xlite v1 Gaming Mouse |
The record
Grouped and collapsible · Tap a group to fold
Performance3▾
| Xlite v4 Mini Gaming Mouse | Xlite v1 Gaming Mouse | |
|---|---|---|
| Max DPI | 32000 DPI | 26000 DPI |
| Sensor | Optical | Optical |
| Weight | 54 g | 52 g |
Design1▾
| Xlite v4 Mini Gaming Mouse | Xlite v1 Gaming Mouse | |
|---|---|---|
| Buttons | 2 | 5 |
Connect1▾
| Xlite v4 Mini Gaming Mouse | Xlite v1 Gaming Mouse | |
|---|---|---|
| Wired | — | ✓ |
Data sources: Amazon
FAQ
Which is better, Xlite v4 Mini Gaming Mouse or Xlite v1 Gaming Mouse?
Xlite v4 Mini Gaming Mouse edges ahead 50 to 49. Choose Xlite v1 Gaming Mouse instead if Weight matters more to you.
What are the main differences?
The main differences: Max DPI (32000 DPI vs 26000 DPI) · Weight (54 g vs 52 g) · Buttons (2 vs 5).
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.
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