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Channel

武汉兰苑《报告》

@wuhan_999

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

18,540subscribers

-2,110 since we began measuring on 8 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1002954585179
TypeChannel
Username@wuhan_999
CreatedBetween 1 August 2025 and 31 October 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded8 August 2026
Last confirmed live19 September 2026
Measurements held32
Confirmed unchanged1 time, most recently 19 September 2026
On Telegramt.me/wuhan_999

Topic

Adult — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 92% 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

18,54020,65019,5958 August 2026 — 20,650 subscribers8 August 2026 — 20,636 subscribers9 August 2026 — 20,611 subscribers10 August 2026 — 20,574 subscribers11 August 2026 — 20,554 subscribers12 August 2026 — 20,520 subscribers13 August 2026 — 20,502 subscribers14 August 2026 — 20,464 subscribers16 August 2026 — 20,420 subscribers17 August 2026 — 20,362 subscribers18 August 2026 — 20,333 subscribers19 August 2026 — 19,680 subscribers20 August 2026 — 19,138 subscribers22 August 2026 — 19,127 subscribers23 August 2026 — 19,099 subscribers25 August 2026 — 19,039 subscribers26 August 2026 — 19,012 subscribers27 August 2026 — 18,993 subscribers28 August 2026 — 18,985 subscribers29 August 2026 — 18,965 subscribers30 August 2026 — 18,939 subscribers31 August 2026 — 18,922 subscribers1 September 2026 — 18,896 subscribers2 September 2026 — 18,871 subscribers3 September 2026 — 18,832 subscribers5 September 2026 — 18,810 subscribers8 September 2026 — 18,750 subscribers11 September 2026 — 18,655 subscribers13 September 2026 — 18,598 subscribers14 September 2026 — 18,592 subscribers16 September 2026 — 18,577 subscribers19 September 2026 — 18,540 subscribers8 August 202619 September 2026
32 measurements spanning 42 days, net -2,110. 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 18,224–20,967 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 32
Measured (UTC)SubscribersChange
19 Sept 2026, 00:5818,540-37
16 Sept 2026, 16:4018,577-15
14 Sept 2026, 21:0018,592-6
13 Sept 2026, 05:1918,598-57
11 Sept 2026, 04:5718,655-95
8 Sept 2026, 04:3618,750-60
5 Sept 2026, 00:1618,810-22
3 Sept 2026, 09:4318,832-39
2 Sept 2026, 02:2618,871-25
1 Sept 2026, 00:4418,896-26
31 Aug 2026, 00:0618,922-17
30 Aug 2026, 02:3418,939-26
29 Aug 2026, 05:5318,965-20
28 Aug 2026, 07:5418,985-8
27 Aug 2026, 06:2618,993-19
26 Aug 2026, 03:3319,012-27
25 Aug 2026, 02:1319,039-60
23 Aug 2026, 14:2819,099-28
22 Aug 2026, 03:5419,127-11
20 Aug 2026, 20:0719,138first reading

Engagement

65 posts held, back to 30 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 57 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
12.8%
avg views ÷ 18,540 subscribers
Avg views / post
2,370
19 posts measured
Reaction rate
0.05%
reactions ÷ views · ER floor
Posts in window
19
of 65 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 3 of 19 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 2 September 2026
Posts held65 (30 July 20262 September 2026)
Views total45,010
Reactions total3
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken3 Sept 2026, 02:11 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

Video runtime
48s
Average length
10s

Measured directly from 5 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

9 reactions across 8 posts, in 2 distinct kinds. The most used accounts for 88.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
888.9%
👍111.1%

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 9 of the 65 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 9 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 65 most recent posts we hold, published 30 July 2026 to 2 September 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

2 Sept 2026, 18:35 UTC≈1,210 viewsread 3 September 2026

#频道互推 #相似推荐 ------------------------------ 📢 南京车神 |【全城精品资源】 📢 武汉摸摸唱商K/拖鞋场KTV 📢 广州上门 📢 站街扫街探店spa 📢 三亚凤凰岛 📢 『粤青楼』楼凤-课室 📢 郑州摩登女郎 📢 约炮实战记录 📢 gay|直男|帅哥|乐园 📢 泉州厦门福州(唐僧)洋酒合集 ------------------------------ ☁️ 互推入口:@SosoCnBot

Signed SOSO搜搜

1 Sept 2026, 10:19 UTC≈1,400 viewsread 3 September 2026
Video

【时间】:2026-09-01 【老师】:米粒 【留名】:匿名 【人照】:9.8 【颜值】:9.8 【身材】:9.6 【服务】:9.5 【态度】:9.5 【环境】:9.7 【综合】:9.65 【过程】:优点确实很年轻,细皮嫩肉该有的都有,胸也很嫩很粉,小穴也是一样的叫的声音好听,小姐姐还说我把她干疼了,缺点就是不爱说话,听小姐姐说刚刚做这个没几天,我也就理解了,下次继续出击

Signed 武汉兰苑管理机器人

1 Sept 2026, 10:03 UTC≈1,260 viewsread 2 September 2026
Photo

TG必备的搜索引擎,快搜kuai帮你发现有趣群组、频道、视频、音乐、电影、新闻 | Find cool stuff all in one bot! 机器人:@kuai @kuaia @kuaiaa 👉 https://t.me/kuai?start=a_3G52IZY

Signed 快搜🔍资源搜索@kuai

1 Sept 2026, 07:49 UTC≈1,410 views1 reactionsread 3 September 2026

🎖精英车评🎖 【时间】:2026-09-01 【老师】:白蝴蝶 【留名】:ShanaJen 【人照】:9.7 【颜值】:9.8 【身材】:10 【服务】:10 【态度】:10 【环境】:10 【综合】:9.92 【过程】:看到硚口这位服务系老师的课表后,内容之丰富、项目之专业直接让我大为震撼,立刻把她加进了关注列表。终于回到武汉,老师整场服务的质量与用心程度,确实让我这个服务体验尚浅的菜鸟彻底被震撼到——说是震撼一整年都毫不夸张。 正式进入正题后,老师全程节奏把控得极好。最后采用后入姿势,出水那一刻老师下面紧紧包裹、温热湿润,再配上她不断输出的骚话与有力的臀浪起伏,快感迅速累积,很快就顺利出水。结束后老师并没有立刻结束,而是细心地为我做了按摩放松,同时一起闲聊几句,氛围轻松愉快,完全没有匆忙或冷场的感觉。 整体来看,老师的服务非常专业,细节到位、情绪价值拉满,无论是技术还是互动都让人十分舒适。喜欢服务系风格的老哥们,千万不

1

Signed 武汉兰苑管理机器人

1 Sept 2026, 02:38 UTC≈1,580 viewsread 3 September 2026
Photo

【时间】:2026-09-01 【老师】:颖儿 【留名】:匿名 【人照】:9.3 【颜值】:9.2 【身材】:9.25 【服务】:9.5 【态度】:10 【环境】:9.5 【综合】:9.46 【过程】:白天提前约了老师,晚上到了后比较符合我的标准,胸不算大但是很圆润,身材很匀称臀部屁股小翘手感不错,特意要LS穿了丝袜,喜欢丝袜摩擦和撕开的感觉很爽。 整个过程体验不错,老师从洗浴到服务还是很贴心,轻声细语的。 技术也挺好,值得CJ

Signed 武汉兰苑管理机器人

31 Aug 2026, 15:37 UTC≈1,320 viewsread 3 September 2026
Photo

🎖精英车评🎖 【时间】:2026-08-31 【老师】:星星 【留名】:sexgogogo 【人照】:9.5 【颜值】:9 【身材】:9 【服务】:9.5 【态度】:9.5 【环境】:9.1 【综合】:9.27 【过程】: 很意外,难得的真人比照片好看的老师。在纸飞机上面被一堆照骗或者人照没关系的工作室狂轰滥炸以后遇到的一个真人好看童颜巨乳的老师,真人脸很小,口的时候还会看着你。很舒服。这个价格这个服务在武汉95里面已经很无敌了。兄弟们冲就行

Signed 武汉兰苑管理机器人

29 Aug 2026, 17:31 UTC≈1,330 views1 reactionsread 3 September 2026

【时间】:2026-08-30 【老师】:白蝴蝶 【留名】:匿名 【人照】:9.9 【颜值】:9.9 【身材】:9.9 【服务】:10 【态度】:10 【环境】:10 【综合】:9.95 【过程】:慕名而来,特意提前几天预约了白老师的✌️课程。第一次见到白老师,她就热情开朗、笑容满面,瞬间把我原本低落的心情彻底带动起来,所有烦恼都被抛到九霄云外。 交完水费后,先舒舒服服洗了个澡。这是我第一次体验异性搓背,手法专业又细致,把全身都清洗得干干净净;日式凳浴更是第一次尝试,感觉新奇又放松,整个过程既私密又舒适。 正式开始后,白老师的按摩手法非常到位,力道恰到好处,揉按之间带着恰到好处的暧昧。她那对大大软软的奶子时不时贴在身上,温热又柔软,触感实在太舒服。花式毒龙的技巧更是一流,深浅交替、节奏变化都掌握得恰到好处,刺激感层层叠加。到了触觉服务环节,那种细腻、敏感的触碰更是让人爽到头皮发麻,几乎瞬间就交代了第一次。 白老师的爱抚和调

1

Signed 武汉兰苑管理机器人

29 Aug 2026, 11:01 UTC≈1,310 viewsread 3 September 2026

【时间】:2026-08-29 【老师】:白蝴蝶 【留名】:匿名 【人照】:9.9 【颜值】:9.8 【身材】:10 【服务】:10 【态度】:10 【环境】:10 【综合】:9.95 【过程】:一进门就看到亲切迎接的LS,陌生感舜间消失,从洗澡到结束超过一小时,顶级服务天花版,先是日式洗澡水中萧再来养生按摩,整个人全放松,接着进入重点,超享受,从没有过的感觉,服务过程超过澳门桑拿,事后还有段按摩,真的值得体验,重点是 LS 超酥软的大胸滑过整个身体,倒立吹萧,顶级超赞,一定再来

Signed 武汉兰苑管理机器人

28 Aug 2026, 13:17 UTC≈3,960 viewsread 3 September 2026

【时间】:2026-08-28 【老师】:琪琪 【留名】:匿名 【人照】:9.3 【颜值】:9.5 【身材】:9.5 【服务】:9.6 【态度】:9.6 【环境】:9.8 【综合】:9.55 【过程】:我是个比较喜欢玩刺激的,今天刚好在榜单上看到琪琪老师,看了课表之后果断约了琪琪老师,要玩就玩舒适,约了pp,老师到酒店之后,我下去接她,看到老师的那一刻,我心中有点小激动,本人穿着黑色上衣加牛仔裤,一下子欲望满山心头,迫不及待的来到房间,琪琪老师比较开朗言谈举止都非常客气。我先去洗个澡,后来老师帮我擦干水,就在卫生间里面开始跟我亲,亲的我老二受不了,老师就跟我玩起了SM,老师的服务很多。各种表演,各种玩具认我选,本人喜欢大,玩SM,老师戴着眼罩,拿着鞭子。经度鞭大,应有尽有,非常刺激的享受, 老师非常配合,课表上的服务只要提出,都会尽量满足,服务项目我就不说了,回去慢慢回味,喜欢SM呢大哥可以冲。

Signed 武汉兰苑管理机器人

26 Aug 2026, 15:01 UTC≈2,790 viewsread 3 September 2026

【时间】:2026-08-26 【老师】:乐瑶 【留名】:匿名 【人照】:9.6 【颜值】:9.8 【身材】:9.9 【服务】:9.8 【态度】:9.9 【环境】:9.8 【综合】:9.8 【过程】:身材:极品身材,天赋怪,碗型腺体大c,娇小乳头,腰线明显,臀部有肉,天生马甲线, 服务:见课表 描述:极品细枝硕果。才下海,羞涩内敛,调教开发潜力大 身材不赘述,确定是才下海几天,总体属于待开发状态。 白纸有白纸的乐趣,服务上生疏,需要给包容和调教的空间。但是白纸的优势就在于,还保留一丝青涩与本能,带来的征服欲是其他不能比拟的。 身体敏感。阴蒂极其敏感,反向服务时开始不吭声,到达阴蒂后,肉眼可见的开始轻哼,轻微颤抖,到大腿夹头,主动迎合颤抖,手臂无处安放,最终主动牵手,可惜要在高潮的前一刻手机突然响,尼玛!我的成就感! 做爱仍有本能反应,虽然反馈内敛羞涩,但悄悄手指抓床单这样的动作,易让人欲罢不能,兽性大发,征服欲拉满。可惜

Signed 武汉兰苑管理机器人

26 Aug 2026, 13:47 UTC≈2,680 viewsread 3 September 2026
Photo

TG必备的搜索引擎,海量资源搜索 海搜 帮你找到、频道、视频、音乐、电影、新闻 | Find cool stuff all in one bot! 海量资源搜索🔍:@haisou 官方频道 @haisou1 官方群聊 @haisou2 👉 https://t.me/haisou?start=a_7506321727

Signed 海搜

26 Aug 2026, 09:18 UTC≈3,090 viewsread 3 September 2026
Photo

【时间】:2026-08-26 【老师】:颖宝 【留名】:匿名 【人照】:8.5 【颜值】:9 【身材】:9 【服务】:9 【态度】:9.3 【环境】:9 【综合】:8.97 【过程】:提前三天约了他时间 今天下午到了他楼下 很好找 遥控我上去 进门老师穿着很性感哦 化着淡妆 交了水费进入浴室洗澡 这几天的秋老虎太厉害了 好热 老师在旁边帮忙 洗完到了床上 因为选的pp所以先现在简单的口完就做了一次 确切的来说我急不可耐了 先是女上 插入碰撞伴随着老师的大奶摇晃🫨 显得非常色情 后续换我后入 伴随着老师娇喘息声 出货 休息一下 继续做服务 挑逗漫游…… 一遍服务一遍聊天 技术很好 舔得我好爽 舌头又软又灵活 口技非常娴熟 一边把玩着他的大胸一边带上套 开始进入 第二次比较久 尝试了各种各样的姿势 最后疯狂输出肉体相互撞击摩擦 完美交货了

Signed 武汉兰苑管理机器人

Showing the 12 most recent of 65 posts we hold for @wuhan_999. 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.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 12 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.

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 19 September 2026 — this entry's latest reading, not the date you are reading this.

“武汉兰苑《报告》” (@wuhan_999), 18,540 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/wuhan_999.

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.