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Channel

深圳茶友老师榜

@AAA6632

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Posts edited after publishing · Citations · Handles named that no longer answer · Cite this entry

34,786subscribers

+8,022 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1002286213550
TypeChannel
Username@AAA6632
Description上榜联系:https://t.me/zhou2666 轮播群:https://t.me/sdffdagh 选妃榜:https://t.me/AAA6632 双向联:@chaoun_bot
CreatedBetween 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live25 October 2026
Measurements held49
Confirmed unchanged1 time, most recently 25 October 2026
On Telegramt.me/AAA6632

Topic

Other / unclassifiable — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 9 September 2026 and assigned it the closest of 31 fixed categories, at 77% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and why it has no browse page of its own yet.

Growth

26,56150,66938,6156 August 2026 — 26,764 subscribers7 August 2026 — 26,761 subscribers8 August 2026 — 26,749 subscribers9 August 2026 — 26,723 subscribers10 August 2026 — 26,710 subscribers11 August 2026 — 26,707 subscribers12 August 2026 — 26,699 subscribers13 August 2026 — 26,662 subscribers14 August 2026 — 26,646 subscribers16 August 2026 — 26,636 subscribers17 August 2026 — 26,597 subscribers18 August 2026 — 26,595 subscribers19 August 2026 — 26,592 subscribers20 August 2026 — 26,595 subscribers21 August 2026 — 26,590 subscribers22 August 2026 — 26,588 subscribers24 August 2026 — 26,581 subscribers25 August 2026 — 26,567 subscribers26 August 2026 — 26,561 subscribers27 August 2026 — 39,564 subscribers28 August 2026 — 39,566 subscribers29 August 2026 — 39,551 subscribers30 August 2026 — 39,564 subscribers31 August 2026 — 39,619 subscribers1 September 2026 — 39,671 subscribers2 September 2026 — 39,576 subscribers4 September 2026 — 39,565 subscribers6 September 2026 — 39,524 subscribers9 September 2026 — 39,494 subscribers12 September 2026 — 39,472 subscribers13 September 2026 — 39,458 subscribers15 September 2026 — 39,443 subscribers17 September 2026 — 39,419 subscribers19 September 2026 — 39,399 subscribers26 September 2026 — 39,352 subscribers4 October 2026 — 50,669 subscribers8 October 2026 — 47,058 subscribers13 October 2026 — 43,376 subscribers14 October 2026 — 41,830 subscribers15 October 2026 — 41,155 subscribers16 October 2026 — 40,848 subscribers17 October 2026 — 39,647 subscribers18 October 2026 — 39,160 subscribers19 October 2026 — 38,550 subscribers20 October 2026 — 37,643 subscribers21 October 2026 — 37,134 subscribers23 October 2026 — 35,909 subscribers24 October 2026 — 35,259 subscribers25 October 2026 — 34,786 subscribers34,7866 August 202625 October 2026
49 measurements spanning 79 days, net +8,022. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 22,945–54,285 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 49
Measured (UTC)SubscribersChange
25 Oct 2026, 01:5634,786-473
24 Oct 2026, 04:4135,259-650
23 Oct 2026, 02:1835,909-1,225
21 Oct 2026, 22:3737,134-509
20 Oct 2026, 15:4637,643-907
19 Oct 2026, 16:4738,550-610
18 Oct 2026, 15:4939,160-487
17 Oct 2026, 15:0639,647-1,201
16 Oct 2026, 12:1540,848-307
15 Oct 2026, 15:1841,155-675
14 Oct 2026, 16:3841,830-1,546
13 Oct 2026, 04:4043,376-3,682
8 Oct 2026, 23:3547,058-3,611
4 Oct 2026, 15:1550,669+11,317
26 Sept 2026, 07:2139,352-47
19 Sept 2026, 13:0039,399-20
17 Sept 2026, 02:1839,419-24
15 Sept 2026, 05:5839,443-15
13 Sept 2026, 18:1639,458-14
12 Sept 2026, 00:3639,472first reading

Engagement

139 posts held, back to 4 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 164 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
1.08%
avg views ÷ 34,786 subscribers
Avg views / post
375
42 posts measured
Reaction rate
0%
reactions ÷ views · ER floor
Posts in window
43
of 139 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 1 of 42 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 24 October 2026
Posts held139 (4 August 2026 – 24 October 2026)
Views total15,744
Reactions total0
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken25 Oct 2026, 04:30 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Photos
≈2,560
Videos
≈550
Links
≈572

Lifetime counters from Telegram’s own channel header, read 25 October 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Video runtime
12m 18s
Average length
11s

Measured directly from 70 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.

Reaction mix

2 reactions across 2 posts, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤2100.0%

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 4 of the 139 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 2 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 139 most recent posts we hold, published 4 August 2026 to 24 October 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

24 Oct 2026, 07:53 UTC44 viewsread 25 October 2026
Photo

坐标:#龙岗 艺名:僖僖 课费:500p 900pp 私聊:@txxx52013 频道:https://t.me/tx52013 双向:@txxx52013_bot 标签:#鸳鸯浴 #舌吻 #六九 #水中箫 #胸推 #深喉 #按摩

24 Oct 2026, 07:39 UTC40 viewsread 25 October 2026
Photo

坐标:#南山 花名:小鱼 课费:700p 1300pp 私聊:@xiaoyu929598 频道:https://t.me/xiaoyu9598 双向:@xiaoyu9598bot 标签:#鸳鸯浴 #水中箫 #舌吻 #六九 #深喉 #丝袜 #制服 #嫩妹

23 Oct 2026, 07:49 UTC72 viewsread 25 October 2026
Photo

坐标:#深圳北站 花名:泥泥 课费:700p 1300pp 私聊:@ninibbaaa 频道:https://t.me/ninibaobb 双向:@ninibaobbbot 标签:#鸳鸯浴 #六九 #口爆 #水中箫 #AB面 #调情 #制服诱惑

23 Oct 2026, 07:02 UTC69 viewsread 25 October 2026
Photo

坐标:龙华 花名:沐沐 课费:600p 1000pp 私聊:@momoyujie520 频道:https://t.me/momoyujie 双向:@momoyujiebot 标签:#舌吻 #六九 #毒龙 #口爆 #指滑 #胸推

23 Oct 2026, 05:10 UTC45 viewsread 24 October 2026
Photo

坐标:#南山 艺名:小仙女 课费:1500p 2600pp 私聊:@sznsxxn2 频道:https://t.me/xxndkunkunwu0 双向:@szxxn_bot 标签:#大胸 #长腿 #丝袜制服 #御姐 #女友感 #白虎

22 Oct 2026, 07:21 UTC76 viewsread 24 October 2026
Photo

坐标:#南山 花名:静静 课费:1000p 1800pp 私聊:@jjy3344 频道:https://t.me/jjy33444 双向:@jjy3344bot 标签:#舌吻 #深喉 #六九 #丝袜 #调情陪浴 #情趣内衣 #水中箫 #jk服

21 Oct 2026, 07:42 UTC86 viewsread 23 October 2026
Photo

坐标:#宝安 花名:沐沐 课费:600p 1000pp 私聊:@zyp168 频道:https://t.me/xiaoyizi8686 双向:@mumufy_bot 标签:#舌吻 #六九 #鸳鸯浴 #丝袜制服 #御姐 #胸推 #漫游 #指滑 #水萧

20 Oct 2026, 08:35 UTC109 viewsread 23 October 2026
Photo

坐标:#宝安 花名:依依 课费:800p 1500pp 私聊:@yiyi9425 频道:https://t.me/guoguo315 双向:@qyt545_bot 标签:#六九 #毒龙 #漫游 #水中萧 #丝袜

20 Oct 2026, 05:58 UTC101 viewsread 23 October 2026
Photo

🌐商户名字:#肥仔甄选(只做精品) 📍服务地区:#广州深圳东莞 💸只做高端,价格:35张起 🎙联系方式: @shenzhenfeizai 🔈选妃频道:@SZfeizai 💬双向机器人: @SZfeizai_bot 🔔营业时间:中午1点➖凌晨6点 👑真正的好资源经得起检验,也经得起时间。 ✨只做高端,只做精品。 不满意包退包换,定金原路返回!

19 Oct 2026, 06:33 UTC131 viewsread 23 October 2026
Photo

坐标: 龙岗 花名:夏天 课费: 700p 1400pp 私聊: @Xiatian_LG 频道: https://t.me/Xiatian_LG66 双向:@LGxiatian6Bot 坐标:#舌吻 #口爆 #水中箫 #毛扫 #胸推 #鸳鸯浴 #制服诱惑 #按摩 #御姐

18 Oct 2026, 06:30 UTC132 viewsread 22 October 2026
Photo

坐标:#宝安 花名:幂幂 课费:环保/880(40分钟) 1188p 1988pp 私聊:@feibao678 频道:https://t.me/feifei9798 双向:@meixue2233bot 标签:#御姐 #舌吻 #鸳鸯浴 #水中箫 #舌尖环游 #制服诱惑 #大长腿

17 Oct 2026, 07:30 UTC120 viewsread 21 October 2026
Photo

坐标:#龙华 花名:茉莉 课费:800p 1600pp 私聊:@MOLI5555Kk 频道:https://t.me/MOMOLLf8885 双向:@mlhcyabot 标签:#舌吻 #六九 #鸳鸯浴 #丝袜制服 #嫩妹 #口爆 #胸推 #三点粉

Showing the 12 most recent of 139 posts we hold for @AAA6632. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Posts edited after publishing

@AAA6632 edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.

An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.

First edit seen
11 September 2026
Most recent edit
11 September 2026

Mentions

Named by 26 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.

Named by

Channels on the register whose posts name this channel's handle.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 25 October 2026 — this entry's latest reading, not the date you are reading this.

“深圳茶友老师榜” (@AAA6632), 34,786 subscribers as measured 25 October 2026. Telegram Register, tgregister.com/channel/AAA6632.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.