Dell E1715S vs Dell E2216HV
Dell E2216HV — Pick the Dell E2216HV — it leads these groups: Display 1 Ergonomics 1
Tap a group name to see the proof · The scoring method is public
The short answer
Dell E2216HV wins this comparison with a score of 56/100, ahead of Dell E1715S (54).
The main differences: Screen size (17 in vs 21.5 in) · Resolution (1280x1024 vs 1920 x 1080 px) · Panel type (TN vs LED-backlit, LCD).
Scores are computed from 8 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
| Dell E1715S | Dell E2216HV | |
|---|---|---|
| Display | 28 | 32 |
| Ergonomics | 89 | 90 |
How to choose
Pick the Dell E2216HV if you care about…
- Screen size 21.5 in +4.5 in vs 17 in
- Weight (with stand) 2812.3 g +937.7 g vs 3750 g
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Where they differ
4 · Only rows that actually differ, with a verdict per row
| Dell E1715S | Dell E2216HV | Where they differ | |
|---|---|---|---|
| Screen size | 17 in | 21.5 in | Dell E2216HV |
| Resolution | 1280x1024 | 1920 x 1080 px | Depends |
| Panel type | TN | LED-backlit, LCD | Depends |
| Weight (with stand) | 3750 g | 2812.3 g | Dell E2216HV |
The record
Grouped and collapsible · Tap a group to fold
Display5▾
| Dell E1715S | Dell E2216HV | |
|---|---|---|
| Screen size | 17 in | 21.5 in |
| Resolution | 1280x1024 | 1920 x 1080 px |
| Response time | — | 5 ms |
| Brightness | — | 200 cd/m² |
| Panel type | TN | LED-backlit, LCD |
Ergonomics3▾
| Dell E1715S | Dell E2216HV | |
|---|---|---|
| Height adjustment | — | ✓ |
| VESA mounting | — | ✓ |
| Weight (with stand) | 3750 g | 2812.3 g |
Data sources: GSMArena
FAQ
Which is better, Dell E1715S or Dell E2216HV?
Dell E2216HV edges ahead 56 to 54 and leads in Display, Ergonomics.
What are the main differences?
The main differences: Screen size (17 in vs 21.5 in) · Resolution (1280x1024 vs 1920 x 1080 px) · Panel type (TN vs LED-backlit, LCD).
How are the scores calculated?
We normalize 8 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.