G-Wolves Fenrir Pro 8K Wireless Gaming Mouse ~18.9g vs G-Wolves Hati HTM Classic Wired Gaming Mouse ~56g
The short answer
G-Wolves Fenrir Pro 8K Wireless Gaming Mouse ~18.9g wins this comparison with a score of 49/100, ahead of G-Wolves Hati HTM Classic Wired Gaming Mouse ~56g (46).
Scores are computed from 6 public spec attributes; missing values stay marked unknown in tables and are imputed at the category median, never passed off as measured.
G-Wolves Fenrir Pro 8K Wireless Gaming Mouse ~18.9g
G-Wolves
At a glance
0–100 per group, normalized within the category · Tap a group for details
| G-Wolves Fenrir Pro 8K Wireless Gaming Mouse ~18.9g | G-Wolves Hati HTM Classic Wired Gaming Mouse ~56g | |
|---|---|---|
| Performance | 62 | 49 |
| Design | 33 | 33 |
| Connect | 63 | 63 |
| Battery | 2 | 4 |
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The record
Grouped and collapsible · Tap a group to fold
Performance3▾
| G-Wolves Fenrir Pro 8K Wireless Gaming Mouse ~18.9g | G-Wolves Hati HTM Classic Wired Gaming Mouse ~56g | |
|---|---|---|
| Max DPI | — | 16000 DPI |
| Sensor | Optical | Optical |
| Weight | — | 56 g |
Design1▾
| G-Wolves Fenrir Pro 8K Wireless Gaming Mouse ~18.9g | G-Wolves Hati HTM Classic Wired Gaming Mouse ~56g | |
|---|---|---|
| Buttons | 6 | 6 |
Connect1▾
| G-Wolves Fenrir Pro 8K Wireless Gaming Mouse ~18.9g | G-Wolves Hati HTM Classic Wired Gaming Mouse ~56g | |
|---|---|---|
| Wired | ✓ | ✓ |
Battery1▾
| G-Wolves Fenrir Pro 8K Wireless Gaming Mouse ~18.9g | G-Wolves Hati HTM Classic Wired Gaming Mouse ~56g | |
|---|---|---|
| Battery life | 40 h | — |
Data sources: Amazon
FAQ
Which is better, G-Wolves Fenrir Pro 8K Wireless Gaming Mouse ~18.9g or G-Wolves Hati HTM Classic Wired Gaming Mouse ~56g?
G-Wolves Fenrir Pro 8K Wireless Gaming Mouse ~18.9g has the higher overall score (49 vs 46).
What are the main differences?
Scores are computed from 6 public spec attributes; missing values stay marked unknown in tables and are imputed at the category median, never passed off as measured.
How are the scores calculated?
We normalize 6 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.