Kingston 16GB DDR4 3200 KVR32N22D8/16 vs Kingston 16GB DDR4 3600
The short answer
Kingston 16GB DDR4 3600 wins this comparison with a score of 39/100, ahead of Kingston 16GB DDR4 3200 KVR32N22D8/16 (37).
The main differences: Memory speed (3200 MT/s vs 3600 MT/s) · CAS latency (16 vs 17).
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.
At a glance
0–100 per group, normalized within the category · Tap a group for details
How to choose
Pick the Kingston 16GB DDR4 3200 KVR32N22D8/16 if you care about…
- CAS latency 16 +1 vs 17
Pick the Kingston 16GB DDR4 3600 if you care about…
- Memory speed 3600 MT/s +400 MT/s vs 3200 MT/s
Best price now
Cheap alternatives
Crucial DDR5 5600
Crucial DDR5 5600 SO-DIMM
ASGARD 16GB 8Gx2 DDR4 3600
JUHOR 32GB DDR5 6000 C40
JUHOR 32GB 16GB*2 DDR5 6000 C40
JUHOR 16GB DDR5 6000 C28
Where they differ
2 · Only rows that actually differ, with a verdict per row
| Kingston 16GB DDR4 3200 KVR32N22D8/16 | Kingston 16GB DDR4 3600 | Where they differ | |
|---|---|---|---|
| Memory speed | 3200 MT/s | 3600 MT/s | Kingston 16GB DDR4 3600 |
| CAS latency | 16 | 17 | Kingston 16GB DDR4 3200 KVR32N22D8/16 |
The record
Grouped and collapsible · Tap a group to fold
Speed2▾
| Kingston 16GB DDR4 3200 KVR32N22D8/16 | Kingston 16GB DDR4 3600 | |
|---|---|---|
| Memory speed | 3200 MT/s | 3600 MT/s |
| CAS latency | 16 | 17 |
Specs3▾
| Kingston 16GB DDR4 3200 KVR32N22D8/16 | Kingston 16GB DDR4 3600 | |
|---|---|---|
| DDR generation | 4 | 4 |
| Module size | 16 GB | 16 GB |
| Voltage | 1.4 V | 1.4 V |
Data sources: Amazon
FAQ
Which is better, Kingston 16GB DDR4 3200 KVR32N22D8/16 or Kingston 16GB DDR4 3600?
Kingston 16GB DDR4 3600 edges ahead 39 to 37. Choose Kingston 16GB DDR4 3200 KVR32N22D8/16 instead if CAS latency matters more to you.
What are the main differences?
The main differences: Memory speed (3200 MT/s vs 3600 MT/s) · CAS latency (16 vs 17).
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.