Jackery Solar Generator 100 Plus vs Jackery Solar Generator 1000 Plus
Jackery Solar Generator 100 Plus — Pick the Jackery Solar Generator 100 Plus — it leads these groups: Power 1
Tap a group name to see the proof · The scoring method is public
The short answer
Jackery Solar Generator 100 Plus wins this comparison with a score of 44/100, ahead of Jackery Solar Generator 1000 Plus (36).
The main differences: Max output (3600 W vs 1500 W) · Weight (35017.1 g vs 10795.4 g).
Scores are computed from 3 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 Jackery Solar Generator 100 Plus if you care about…
- Max output 3600 W +2100 W vs 1500 W
Pick the Jackery Solar Generator 1000 Plus if you care about…
- Weight 10795.4 g +24221.7 g vs 35017.1 g
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Where they differ
2 · Only rows that actually differ, with a verdict per row
| Jackery Solar Generator 100 Plus | Jackery Solar Generator 1000 Plus | Where they differ | |
|---|---|---|---|
| Max output | 3600 W | 1500 W | Jackery Solar Generator 100 Plus |
| Weight | 35017.1 g | 10795.4 g | Jackery Solar Generator 1000 Plus |
The record
Grouped and collapsible · Tap a group to fold
Power2▾
| Jackery Solar Generator 100 Plus | Jackery Solar Generator 1000 Plus | |
|---|---|---|
| Max output | 3600 W | 1500 W |
| AC outlets | — | 3 |
Design1▾
| Jackery Solar Generator 100 Plus | Jackery Solar Generator 1000 Plus | |
|---|---|---|
| Weight | 35017.1 g | 10795.4 g |
Data sources: Amazon
FAQ
Which is better, Jackery Solar Generator 100 Plus or Jackery Solar Generator 1000 Plus?
Jackery Solar Generator 100 Plus has the higher overall score (44 vs 36) and leads in Power. Choose Jackery Solar Generator 1000 Plus instead if Weight matters more to you.
What are the main differences?
The main differences: Max output (3600 W vs 1500 W) · Weight (35017.1 g vs 10795.4 g).
How are the scores calculated?
We normalize 3 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.
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