科技美学

科技美学

@kjmx
UCAC204niCVvtDRDFYSiK7Cg Created on YouTube: 27.03.2013 Chinese Lifestyle Open on YouTube
First seen in analytics: 09.04.2026
Subscribers
96 000
+700 / 30d
Views
12 378 305
+596 353 / 30d
Videos
1 154
+29 / 30d
Global Rank
#3,769
Language Rank
#170
Chinese
Topic Rank
#1,183
Lifestyle
Est. Monthly Earnings
$894 – $2,683
Based on 30-day views × topic CPM

Date

Date Subscribers ± Views ± Videos ±
2026-08-14 95 300 — 11 781 952 — 1 125 —
2026-08-15 95 300 0 11 783 887 +1 935 1 126 +1
2026-08-18 95 300 0 11 791 726 +7 839 1 127 +1
2026-08-19 95 300 0 11 794 297 +2 571 1 128 +1
2026-08-24 95 300 0 11 805 364 +11 067 1 128 0
2026-08-26 95 300 0 11 807 117 +1 753 1 128 0
2026-08-28 95 300 0 11 809 813 +2 696 1 129 +1
2026-09-01 95 300 0 11 843 686 +33 873 1 132 +3
2026-09-03 95 300 0 11 847 025 +3 339 1 131 -1
2026-09-06 95 400 +100 11 850 620 +3 595 1 134 +3
2026-09-09 95 500 +100 11 853 400 +2 780 1 138 +4
2026-09-11 95 600 +100 12 042 142 +188 742 1 141 +3
2026-09-13 95 600 0 12 059 816 +17 674 1 141 0
2026-09-15 95 600 0 12 066 258 +6 442 1 141 0
2026-09-17 95 600 0 12 069 363 +3 105 1 144 +3
2026-09-18 95 700 +100 12 082 392 +13 029 1 145 +1
2026-09-20 95 800 +100 12 157 223 +74 831 1 145 0
2026-09-22 95 800 0 12 188 868 +31 645 1 145 0
2026-09-23 95 800 0 12 199 816 +10 948 1 146 +1
2026-09-25 95 900 +100 12 233 275 +33 459 1 148 +2
2026-09-27 95 900 0 12 258 500 +25 225 1 148 0
2026-09-28 95 900 0 12 262 201 +3 701 1 149 +1
2026-10-01 95 900 0 12 297 283 +35 082 1 151 +2
2026-10-05 95 900 0 12 318 725 +21 442 1 151 0
2026-10-06 95 900 0 12 320 613 +1 888 1 151 0
2026-10-09 95 900 0 12 332 917 +12 304 1 152 +1
2026-10-11 95 900 0 12 348 202 +15 285 1 152 0
2026-10-13 96 000 +100 12 360 524 +12 322 1 153 +1
2026-10-15 96 000 0 12 377 908 +17 384 1 154 +1
2026-10-16 latest 96 000 0 12 378 305 +397 1 154 0
Daily Average 13 10 066 0
Weekly Average 47 37 810 1
Last 14 days 100 81 022 3
Last 30 days 400 312 047 13

Charts and Forecast for the Channel 科技美学

About the Channel Growth Forecast 科技美学: The forecast is based on linear regression of historical data and is intended for reference purposes only.

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