ASRock X870 Taichi Creator vs ASRock X870E Nova WiFi
The short answer
ASRock X870 Taichi Creator wins this comparison with a score of 61/100, ahead of ASRock X870E Nova WiFi (57).
The main differences: Max memory OC (8000 MHz vs 8200 MHz).
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.
At a glance
0–100 per group, normalized within the category · Tap a group for details
| ASRock X870 Taichi Creator | ASRock X870E Nova WiFi | |
|---|---|---|
| Memory | 73 | 58 |
| Connectivity | 79 | 79 |
| Audio | 100 | 100 |
How to choose
Pick the ASRock X870E Nova WiFi if you care about…
- Max memory OC 8200 MHz +200 MHz vs 8000 MHz
Best price now
Cheap alternatives
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ASUS Asus ROG Crosshair X870E Edition 20
ASUS Asus ROG Crosshair X870E Apex
Where they differ
1 · Only rows that actually differ, with a verdict per row
| ASRock X870 Taichi Creator | ASRock X870E Nova WiFi | Where they differ | |
|---|---|---|---|
| Max memory OC | 8000 MHz | 8200 MHz | ASRock X870E Nova WiFi |
The record
Grouped and collapsible · Tap a group to fold
Memory2▾
| ASRock X870 Taichi Creator | ASRock X870E Nova WiFi | |
|---|---|---|
| Memory slots | 4 | 4 |
| Max memory OC | 8000 MHz | 8200 MHz |
Expansion1▾
| ASRock X870 Taichi Creator | ASRock X870E Nova WiFi | |
|---|---|---|
| PCIe x16 slots | 0 | 0 |
Connectivity2▾
| ASRock X870 Taichi Creator | ASRock X870E Nova WiFi | |
|---|---|---|
| Fan headers | 7 | 7 |
| Bluetooth | 5.4 | 5.4 |
Audio1▾
| ASRock X870 Taichi Creator | ASRock X870E Nova WiFi | |
|---|---|---|
| Audio SNR | 130 dB | 130 dB |
Data sources: GSMArena
FAQ
Which is better, ASRock X870 Taichi Creator or ASRock X870E Nova WiFi?
ASRock X870 Taichi Creator has the higher overall score (61 vs 57). Choose ASRock X870E Nova WiFi instead if Max memory OC matters more to you.
What are the main differences?
The main differences: Max memory OC (8000 MHz vs 8200 MHz).
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.