TS-G1N TS-G1N vs TS-G3NL TS-G3NL
The short answer
It's a close call: TS-G1N TS-G1N / TS-G3NL TS-G3NL both land at 56/100.
Scores are computed from 4 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
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The record
Grouped and collapsible · Tap a group to fold
Design2▾
| TS-G1N TS-G1N | TS-G3NL TS-G3NL | |
|---|---|---|
| Layout | 全尺寸式 | 全尺寸式 |
| Key count | 104 | 104 |
Connect1▾
| TS-G1N TS-G1N | TS-G3NL TS-G3NL | |
|---|---|---|
| 2.4GHz wireless | — | — |
Feel1▾
| TS-G1N TS-G1N | TS-G3NL TS-G3NL | |
|---|---|---|
| Switch type | 机械轴（黑轴），机械轴（红轴），机械轴（茶轴），机械轴（青轴） | 机械轴（黑轴），机械轴（红轴），机械轴（茶轴），机械轴（青轴） |
Data sources: GSMArena
FAQ
Which is better, TS-G1N TS-G1N or TS-G3NL TS-G3NL?
It's a close call: TS-G1N TS-G1N / TS-G3NL TS-G3NL both land at 56/100.
What are the main differences?
Scores are computed from 4 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 4 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.