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Google Daydream View vs Google DayDream View (2017)

🏆 Settled

Google Daydream View — Pick the Google Daydream View — it leads these groups: Design 1

Tap a group name to see the proof · The scoring method is public

The short answer

Google Daydream View wins this comparison with a score of 40/100, ahead of Google DayDream View (2017) (36).

The main differences: Weight (220 g vs 261 g).

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.

🏆 Overall winner Google Daydream View

Google Daydream View

Google
40score / 100
1 win · 3 tied PCMag ★ 3.5
Google DayDream View (2017)

Google DayDream View (2017)

Google
36score / 100
0 wins · 4 tied

At a glance

0–100 per group, normalized within the category · Tap a group for details

Google Daydream ViewGoogle DayDream View (2017)
Display 54 45
Design 86 80

How to choose

Pick the Google Daydream View if you care about…

  • Weight 220 g +41 g vs 261 g

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Where they differ

1 · Only rows that actually differ, with a verdict per row

Google Daydream ViewGoogle DayDream View (2017)Where they differ
Weight 220 g261 g Google Daydream View

The record

Grouped and collapsible · Tap a group to fold

Display1▾
Google Daydream ViewGoogle DayDream View (2017)
Field of view — 100 °
Battery1▾
Google Daydream ViewGoogle DayDream View (2017)
Battery 220 mAh 220 mAh
Design1▾
Google Daydream ViewGoogle DayDream View (2017)
Weight 220 g 261 g
Connectivity1▾
Google Daydream ViewGoogle DayDream View (2017)
Bluetooth 4 4

Data sources: GSMArena

FAQ

Which is better, Google Daydream View or Google DayDream View (2017)?

Google Daydream View has the higher overall score (40 vs 36) and leads in Design.

What are the main differences?

The main differences: Weight (220 g vs 261 g).

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.