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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.

🏆 Overall winner Xlite v4 Mini Gaming Mouse

Xlite v4 Mini Gaming Mouse

Pulsar
50score / 100
1 win · 3 tied
Xlite v1 Gaming Mouse

Xlite v1 Gaming Mouse

Pulsar
49score / 100
3 wins · 1 tie

At a glance

0–100 per group, normalized within the category · Tap a group for details

Xlite v4 Mini Gaming MouseXlite 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 —

Best price now

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Where they differ

4 · Only rows that actually differ, with a verdict per row

Xlite v4 Mini Gaming MouseXlite v1 Gaming MouseWhere they differ
Max DPI 32000 DPI26000 DPI Xlite v4 Mini Gaming Mouse
Weight 54 g52 g Xlite v1 Gaming Mouse
Buttons 25 Xlite v1 Gaming Mouse
Wired —✓ Xlite v1 Gaming Mouse

The record

Grouped and collapsible · Tap a group to fold

Performance3▾
Xlite v4 Mini Gaming MouseXlite v1 Gaming Mouse
Max DPI 32000 DPI 26000 DPI
Sensor Optical Optical
Weight 54 g 52 g
Design1▾
Xlite v4 Mini Gaming MouseXlite v1 Gaming Mouse
Buttons 2 5
Connect1▾
Xlite v4 Mini Gaming MouseXlite 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.