【广州茶馆】:https://t.me/gzcg9 【时间】:2026-08-07 【老师】:苏媚 【账号】:@qq885186 【留名】:匿名 【颜值】:风骚御姐脸型好看 【身材】:胸大身材顶 【罩杯】:C+ 【服务】:服务热情主动 【态度】:态度很好情绪价值拉满 【位置】:天河猎德 【评分】:9.1 【过程】:定金约好老师,开车直接进车库好停车,联系老师上去见面是我喜欢的类型,御姐 翘臀 大奶接着默契地交钱,洗澡。冲澡完毕,她还会很贴心地帮忙擦拭后背,这很加分了,进屋后看着她脱掉衣服,那个妩媚的眼神丰满的身材看着都带劲。开始用手撸动我的鸡巴,一阵舒服的感觉传来。她屁股和腰的皮肤状态真的很好,肯定每天睡前都有好好地涂身体乳。接着她往下开始舔我的胸,而且被舔胸时也没有口水味,就很棒。 感觉越来越刺激,我的鸡巴已经硬顶着她的腿好久了,她想接着用与以往不同的姿势给我口,不过我憋了一周被她这样挑逗真的忍不住了,直接戴套插入…

Channel
苏媚频道
@Smnb8818
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
3,312subscribers
+267 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
Register entry
| Telegram ID | -1003907033040 |
|---|---|
| Type | Channel |
| Username | @Smnb8818 |
| Created | Between 1 April 2026 and 11 July 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 11 August 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 11 August 2026 |
| On Telegram | t.me/Smnb8818 |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Aug 2026, 14:12 | 3,312 | +215 |
| 8 Aug 2026, 04:36 | 3,097 | +52 |
| 7 Aug 2026, 13:31 | 3,045 | no change |
| 7 Aug 2026, 12:32 | 3,045 | first reading |
Engagement
17 posts held, back to 11 July 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 2 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 16.2%
- avg views ÷ 3,312 subscribers
- Avg views / post
- 537
- 10 posts measured
- Reaction rate
- 0.202%
- reactions ÷ views · ER floor
- Posts in window
- 11
- of 17 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 10 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 7 August 2026 |
|---|---|
| Posts held | 17 (11 July 2026 – 7 August 2026) |
| Views total | 5,372 |
| Reactions total | 4 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 8 Aug 2026, 00:09 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
- 15s
- Average length
- 8s
Measured directly from 2 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
10 reactions across 7 posts, in 2 distinct kinds. The most used accounts for 90.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 9 | 90.0% | |
| 🔥 | 1 | 10.0% |
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 7 of the 17 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 10reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 17 most recent posts we hold, published 11 July 2026 to 7 August 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
本群独家合作伙伴 【糖心app】台湾知名视频网站(麻豆传媒同级) 【51品茶(51茶馆)】国内最大修车平台 全广州活动最多,真人最多,狼友最活跃的群! https://telegram.me/gzcg9
苏媚频道 pinned a photo
🎉 广州茶馆-苏媚半价券 🎁 奖品清单 • p半价券(必须写报告) × 1 🛡️ 参与条件 • 加入 广州茶馆 • 加入 广州茶馆-在榜老师(新榜) • 加入 苏媚频道 • 必须设置用户名 🔮 祝福加持 • 祝福消耗:5圣晶石 • 祝福上限:无上限次 • 祝福一次增加一个抽奖号,提高中奖率 • 幸运值祝福:支持 幸运值说明 ⌛ 抽选时刻 • 2026-08-11 19:45:00 📜 抽奖说明 1:刷屏、灌水、纯表情、复制粘贴、无意义对话、删除消息等,一律视为无效发言,取消中奖资格!请用心交流! 2:中奖后7天内出击,完成必须写报告!没出报告的拉黑抽奖!写报告:@gzcg1bot 3:写报告抽500现金和巨量圣晶石!!! 兑奖 @qq885186 ✨ 愿命运之剑指引你们前行,直至胜利之光照耀每一个人。
❤1
【嫩妹报告】https://t.me/GZNMHEJI 【老师艺名】 苏媚 【联系方式】@qq885186 【所在位置】天河 【验证留名】圣级长度 【验证时间】7/28 【修车费用】1000p 【颜值身材】9 【服务内容】 课表 丝袜 高跟 制服 情趣 【服务态度】 热情态度很好 【优点缺点】风骚 身材好 胸大 骚浪 【推荐程度】 9 【体验细节】 提前和苏媚老师约了时间提前了几分分钟到,地方很好找,进来没门禁。进门以后苏媚老师很温柔的给了一个拥抱,然后就去洗澡,出来就躺在床上进行服务。 老师穿着马油质感丝袜感觉不错,挺骚的。服务胸推 屁股 丝袜 高跟 情趣,舌吻 69 都是搞了一遍,老师的眼神很骚,骚话很多,让人很兴奋。老师口技不错,有深喉,大概口了几分钟然后女上,老师不断前后摩擦,太他妈的爽了,没控制住,被老师轻松拿下,水很多挺润。喜欢御姐冲,性价比很高。 ♥️温馨提示: 以上仅代表个人体验,报告仅供参考! 👎🏿府上专员严…
宝宝们,上课啦。🌹
宝宝们上课了,黑丝 情趣 高跟准备好了🌹😘
【嫩妹报告】https://t.me/GZNMHEJI 【老师艺名】 苏媚 【联系方式】@qq885186 【所在位置】天河 【验证留名】 老鸟 【验证时间】7/19 【修车费用】1600p 【颜值身材】9 【服务内容】 课表 舌吻 口爆 69 【服务态度】 热情态度很好 【优点缺点】风骚御姐 身材好 胸大 服务超级好 【推荐程度】 9 【体验细节】 本来约了另外一个老师,到地方罚站20分钟,给我整无语了,又联系了苏媚老师正好老师有空直接上楼,看到老师本人,美颜了一点,本人高挑丰满,前凸后翘,长腿大奶风骚御姐一枚,果断付了课费,苏媚老师情商很高,沟通能力很强,喜欢闻着老师身上淡淡的香水味,凑近我开始调戏我啊,隔着裤子给我直接摸鼓包了,之后就带我去洗澡,洗干净了还给我来了一段水中萧,该不说不说ls的口活是十分的nice,洗完之后老师还给我耐心的擦干,过了一会就去床上做服务了该有的服务,该不说不服务是真的很不错,第一次直接给我口爆…
❤1🔥1
宝宝们开课了🌹😘
【广州茶馆】:https://t.me/gzcg9 【时间】:2026-07-20 【老师】:苏媚 【账号】:@qq885186 【留名】:匿名 【颜值】:风骚御姐风,颜值在线。 【身材】:高挑,丰满,腿长。 【罩杯】:C+ 【服务】:课表 【态度】:高情商 情绪价值高 态度好 【位置】:天河猎德 【评分】:9 【过程】:跟老师约了课 就在附近就直接过去了!到了老师课室楼下指挥遥控上楼后 进门看到老师穿的很性感🫦 身材很棒 更性感,丰满翘臀,口水都快流出来了 课室环境很不错!看得出来老师是个对生活质量挺高的那种 然后聊了会交了水费就开始脱衣洗澡了🛁 老师帮忙洗顺便拿着凶器一直诱惑我 感觉像那种半夜约见情人的场景 洗完澡后老师有问我要不要穿丝袜这些 然后就开始帮我按了一下摩开始了他的服务 用奶子推了下全身 然后就深喉我的小兄弟 差点儿就给老师缴械了 然后我让老师慢点 老师很耐心的慢慢来 等小兄弟想战斗了就带上好装备 就开始战斗 我…
打桩报告:https://t.me/GZFYJT 验证留名:匿名 验证时间:7.15 身材颜值:8 修车水费:1000p 服务内容:课表上都有 体验细节 :抽到苏媚老师的半价券,和老师约好时间,到点到步老师遥控上楼,进门见到老师,高颜值御姐,身材好到不行,举止大方得体,皮肤超白白嫩嫩。在沙发上坐定定先交上水费,老师很热情给我来瓶水,喝上一口再宽衣解带陪同一起洗澡,洗完澡上床,让我完全放松,开始服务,全身舔得很仔细,唇舌和胸部特别灵活,在我背上来回摩擦,又软又滑,这是我碰过的最好的服务,口技非常不错,没有明显齿感,可以一直狂口,差点就…
❤1
苏媚频道 pinned a photo
Showing the 12 most recent of 17 posts we hold for @Smnb8818. 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.
Citation-graph rank
Citation-graph rank — 580,208 of 1,169,250entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
Forward network
Republishes
Channels on the register whose posts this channel has forwarded.
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 2 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.
Named by
Channels on the register whose posts name this channel's handle.
Names
Channels on the register whose handles appear in this channel's posts.
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 11 August 2026 — this entry's latest reading, not the date you are reading this.
“苏媚频道” (@Smnb8818), 3,312 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/Smnb8818.
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.