Ducky One 3 SF vs AJAZZ AK820 Pro
AJAZZ AK820 Pro — Pick the AJAZZ AK820 Pro — it leads these groups: Design 1
Tap a group name to see the proof · The scoring method is public
The short answer
AJAZZ AK820 Pro wins this comparison with a score of 68/100, ahead of Ducky One 3 SF (65).
The main differences: Layout (65% vs ANSI (United States)) · Weight (1000 g vs 800 g) · Switch type (Cherry MX (hot-swap) vs Ajazz Gift Switch).
Scores are computed from 10 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
How to choose
Pick the AJAZZ AK820 Pro if you care about…
- Weight 800 g +200 g vs 1000 g
Best price now
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Where they differ
3 · Only rows that actually differ, with a verdict per row
| Ducky One 3 SF | AJAZZ AK820 Pro | Where they differ | |
|---|---|---|---|
| Layout | 65% | ANSI (United States) | Depends |
| Weight | 1000 g | 800 g | AJAZZ AK820 Pro |
| Switch type | Cherry MX (hot-swap) | Ajazz Gift Switch | Depends |
The record
Grouped and collapsible · Tap a group to fold
Design5▾
| Ducky One 3 SF | AJAZZ AK820 Pro | |
|---|---|---|
| Layout | 65% | ANSI (United States) |
| Hot-swappable | ✓ | ✓ |
| Per-key RGB | ✓ | ✓ |
| Key count | 68 | — |
| Weight | 1000 g | 800 g |
Connect3▾
| Ducky One 3 SF | AJAZZ AK820 Pro | |
|---|---|---|
| Wired | ✓ | — |
| Bluetooth | — | — |
| 2.4GHz wireless | — | — |
Feel1▾
| Ducky One 3 SF | AJAZZ AK820 Pro | |
|---|---|---|
| Switch type | Cherry MX (hot-swap) | Ajazz Gift Switch |
Value1▾
| Ducky One 3 SF | AJAZZ AK820 Pro | |
|---|---|---|
| Price | 120 USD | — |
FAQ
Which is better, Ducky One 3 SF or AJAZZ AK820 Pro?
AJAZZ AK820 Pro has the higher overall score (68 vs 65) and leads in Design.
What are the main differences?
The main differences: Layout (65% vs ANSI (United States)) · Weight (1000 g vs 800 g) · Switch type (Cherry MX (hot-swap) vs Ajazz Gift Switch).
How are the scores calculated?
We normalize 10 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.