Channel
@qljb20
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
10,063subscribers
+4,070 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1002470692954 |
|---|---|
| Type | Channel |
| Username | @qljb20 |
| Created | Between 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 9 September 2026 |
| Measurements held | 17 |
| Confirmed unchanged | 1 time, most recently 9 September 2026 |
| On Telegram | t.me/qljb20 |
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 11 September 2026 and assigned it the closest of 31 fixed categories, at 65% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 9 Sept 2026, 12:55 | 10,063 | +18 |
| 6 Sept 2026, 02:17 | 10,045 | +9 |
| 4 Sept 2026, 01:19 | 10,036 | +20 |
| 2 Sept 2026, 13:26 | 10,016 | +27 |
| 30 Aug 2026, 20:57 | 9,989 | +39 |
| 27 Aug 2026, 20:02 | 9,950 | +28 |
| 25 Aug 2026, 03:47 | 9,922 | +23 |
| 21 Aug 2026, 16:15 | 9,899 | -397 |
| 20 Aug 2026, 13:24 | 10,296 | +5 |
| 19 Aug 2026, 12:02 | 10,291 | +10 |
| 18 Aug 2026, 14:44 | 10,281 | +6 |
| 17 Aug 2026, 12:15 | 10,275 | +6 |
| 16 Aug 2026, 02:17 | 10,269 | +186 |
| 14 Aug 2026, 09:55 | 10,083 | +4,001 |
| 10 Aug 2026, 22:27 | 6,082 | +85 |
| 7 Aug 2026, 17:01 | 5,997 | +4 |
| 6 Aug 2026, 22:46 | 5,993 | first reading |
17 posts held, back to 21 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 30 pages of Telegram’s post history, 20 posts per page.
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 5 of 8 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 28 August 2026 |
|---|---|
| Posts held | 17 (21 July 2026 – 28 August 2026) |
| Views total | 16,015 |
| Reactions total | 9 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 29 Aug 2026, 04:32 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.
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.
45 reactions across 14 posts, in 1 kind.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 45 | 100.0% |
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 14 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 45 reactions 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 21 July 2026 to 28 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.
#南山 #雨桐 #1000p ❓ 课表差异点 课表很实诚，该有的都有 😀 优点 性格好服务好态度好，亲和力强，广东妹子，颜值中等往上。非常照顾根据你的喜好出发，希望你舒服的那种。很主动很骚，口活胸推都会结合手感受不错，臀腰比也ok，做爱过程配合度高，结束完还有按摩，整个下来自然不生硬 👏 缺点 胸科技介意的注意，矮个子但比例佳，些许纹身因人而异，正常黄肤 📱 出击经历 跟雨桐老师渊源挺大，相互前前后后错开了很多次，都是时间对不上，几个月怕是有了😂这次防止意外发生，早早就提前到了，如期上门。老师非常热情并且调侃了终于见面了，然后递水小小的挑逗了下然后去洗澡，洗澡老师也狠狠的调情了，胸推，舔胸，口，浴室就已经旱地拔葱相当硬了。上了床，老师也是前戏占比多，各种小招式小口活把你干硬，然后戴套，换了多个体位，此间细节就不说了，顺利出水，因为我没坚持多久、进门到结束就20来分钟。事后老师给我按摩了挺久、愉快结束。 😎 青楼是否认证…
#南山 #辛迪 #1300p ❓ 课表差异点 正常黄肤，c胸 😀 优点 颜值好看的嫩姐，人照应该有8.5-9，大长腿，胸挺，不是很瘦微肉属于好日的身材，舔耳朵很舒服，说话江苏女子比较温柔，人很热情带骚，全自动，镜子加分，很客气 👏 缺点 肤色正常黄肤，很会夹主动强行夹，没几下就得交代，过于厉害 📱 出击经历 从另外一个老师推荐过来，见到老师第一眼，觉得老师很好看，讲话也很温柔，递水拖鞋后就进去洗漱，老师应该有点小洁癖，不管是洗身子还是上了床能感觉老师属于爱干净那种。老师前戏调情很足，尤其舔耳朵让人麻麻的，舌头也是上下游走很灵活，主动让我抓胸摸小穴，不一会🐔就硬的不行，老师主动进来后女上，真的太会夹了… 前前后后上上下下，根本扛不住几下，换了推车，感觉没几步就得交代。最后憋着一口气在大镜子面前加速交代了，只能说在老师身材和技术双持下，很难多享受一些😂 😎 青楼是否认证 已认证 🏅 青楼等级 淑妃 上 ➡️ 直通…
❤1
#南山 #豆豆 #1300p ❓ 课表差异点 胸a+到b，其他基本吻合 😀 优点 大长腿，长得比较精致（淡妆前妆应该属于颜值高的类型） ，叫声很好听（这点加分），很自然，卧室很温馨可爱 👏 缺点 胸小，可以理解真的是筷子腿很瘦，正常黄皮，抽到粮票还是很划算，全价的话小贵 📱 出击经历 之前很早很早就在粮票抢到了豆豆老师的半价券，但是之前老师休息了，这次回来开课老师也私信告诉我，我马上就启动了。天还下着大雨，可能运气比较好，到了科室雨就停了。进门第一眼就感觉老师很高很瘦，我立马说了一句你真的好瘦真的筷子腿，老师是淡妆给人很自然不是整容脸，相信全妆应该挺好看，交了水费，由于浴室比较小，我就自己先洗了。进了卧室满满的可爱风，看起来很干净整洁。因为晚上比较晚，我就躺下等着老师服务，正常的上下服务咨询我要不要进来，我感觉也挺好就让老师进来了。老师在上不是很熟练慢慢的，能感觉到老师比较紧，上摇了一会就换我操盘。老师叫声出乎我意料的好…
❤3
#南山 #➕1 #1300p ❓ 课表差异点 服务很多唯数不多该有都有的，这个点赞 😀 优点 颜值不错，眼睛大，有点异域长相，最突出呀优点就是口活（舌头大特别灵活），倒立/对着镜子倒挂/水中萧/回龙萧/你能想到的她都没问题，无齿感带深喉，床上功夫了得，你是木桩不动也没问题，性爱魅力强，配合度高健谈，胸很柔软摸着很舒服，小c，小马甲线 👏 缺点 黄皮，胸很不错奶头不粉，个子不高157左右，感觉老师应该有小抽脂但是不妨碍 📱 出击经历 是个频道主和水友同时推荐，看到频道里老师的花样口活，确实来了兴趣，于是约了老师。开门眼前其实比我预期高，我以为老师颜值不咋滴实际属于中偏上一点点，带点异域长相，可能眼睛大原因。老师起初状态不是很好，聊了几句，可能是情绪恢复了很多，于是就正常洗漱上床。如频道所说，洗澡就开始一顿口活，老二根本扛不住的硬。上床之后选了个制服，于是老师就开始了她的表演，老师舌头真的好大好灵活，一下子能舔/包裹所有。尤…
#南山 #薇薇 #850p ❓ 课表差异点 无 😀 优点 嫩妹，舌吻舌到饱，口的时候不喊停，不会停，女上很强，体力很好，做爱反馈会有迷离的感觉，态度非常好和配合 👏 缺点 肩膀后有个纹身，胸A接近B，妆比较浓 📱 出击经历 看频道以为是微胖型嫩妹，进门看到实际身材不算微胖，正常身材，虽然胸不大，但是腰无赘肉，屁股也大，洗浴认真，会努力找话题聊天，口技还可以，操盘听话，女上可以坚持好一会，会返 😎青楼是否认证 已认证 🏅青楼等级 淑妃 中往下一点 ➡️直通车 @sznsww
❤2
#南山 #莹莹 #1100p ❓ 课表差异点 和课表无差异 😀 优点 嫩妹，中偏上颜值，和认证视频没什么差异，声音软甜，做爱反馈佳，很配合，有情绪价值自然，胸b但很挺，情到深处小性瘾，值得打个卡 👏 缺点 正常黄皮，皮肤可能不适应不光滑，小小贵（已降价 📱 出击经历 毛遂自荐的老师，南山著名科室了，算是比较熟悉。开门第一印象就是和视频差异不大，颜值很高，挺嫩的妹子。有点赶时间也没多聊就洗澡了，洗完上床没立刻进入正题因为挺冷，拥抱并扯了下犊子，老师手很自然的就过来了，很听话服务也属于那种小猫咪的感觉，很自然，相互调戏了下就直接来了，我觉得体验最佳的事做爱过程，老师的反馈特别好很自然不做作，而且情到深处是那种很想要的变得自己很主动，配合度也很高，换了多个姿势，本来想找我喜欢的大镜子接住战斗，最后选择了老师喜欢的后入，对着窗台看外面（也算有镜子）愉快结束了战斗 😎 青楼是否认证 已认证 🏅 青楼等级 淑妃 上 ➡️…
❤2
#福田 #锦锦 #1000p ❓ 课表差异点 课表该有的都有，不夸张 😀 优点 颜值高，情绪价值很足，懂做爱，各种姿势都能满足，视觉效果也是很棒的 👏 缺点 黄皮，胸略小，课室空调不太冷 📱 出击经历 很幸运抽到青楼的半价，于是提前和老师约好，来了一看果然没失望，进门递水，付了一课水费，老师一起陪洗，出来开始服务，穿上制服丝袜，开始服务，口的很舒服，没有齿感，很会调情找感觉，能看出来老师也很享受，并不是装的，进入正题，进入的感觉非常顺滑，中间甚至有噗得一声，搞得我以为是掉出来了......传教士和后入都尝试了，传教士的时候把ls的美腿扛在肩上，低头就能看到美腿和高跟鞋，像艺术品一样；后入的时候ls翘臀软肉直晃，我也没忍住直接交货了。非常爽，姐姐各方面我都很满意，有机会肯定会再去上课的哈哈哈。 😎 青楼是否认证 已认证 🏅 青楼等级 淑妃 中偏上一丢丢 ➡️ 直通车 https://t.me/jinjinxiaow
❤1
#南山 #竹眠 #800p ❓ 课表差异点 正常肤色黄皮、无制服 😀 优点 人照9分，颜值高，胸C-很软，皮肤光滑，身材好。会聊天不会冷场，听话敬业，水多，反馈真实不假叫，舌到饱。 👏 缺点 手臂有一点纹身/抽烟（看自己是否认为缺），女上比较菜，没制服 📱 出击经历 课室在南山区著名景点，遥控上门。不用刷卡，课室环境不错，老师穿着睡衣，看脸是个颜值高的嫩妹，人照9分吧。小老弟微微一硬略表致敬。交了水费，叫老师往沙发上一坐边和老师聊天边上下其手。胸手感很软，然后和老师去浴室，完全不用我动手帮我洗的干干净净。给老二洗的邦邦硬。然后搂着老师上床，别的先不管先舌了起来不错老师会回应，很享受。摸摸亲亲然后传教士起手，老师很敏感，叫的也真实，水也多。看着老师手紧紧抓着床单，差点顶不住，赶紧换后入，屁股大又软，是个好炮架，1234，2234。听着老师的叫声顶不住了，换正面加一波攻速，出水了，值得在返。 😎 青楼是否认证 已认证 🏅…
#南山 #小舞 #800p ❓ 课表差异点 没什么差别，本身课表也没太多花哨的，嫩妹也是如此 😀 优点 嫩，身材硬件是可以的，165长腿，苗条但有肉，天然胸b+到c-，很挺足够握住，颜值几乎和照片没差只是没那么白，害羞但是很听话，水多，相比其他嫩妹能自己操盘（频道照片纹身是贴的），性价比拉满，如果只是快餐吃嫩600… 👏 缺点 没啥服务，口活不太行要慢慢调教，黄皮肤偏一点黑，必须要白皮的避 📱 出击经历 实在是某人强烈推荐，最近很少吃新人，因为自己不喜欢当工兵因为我也怕雷。再某人的强烈保证下我就去试试，有点不巧，我到的时候老师也刚到，房间刚开有点热，老师看得出来有些紧张，先开空调让房间冷下来，然后过程中闲聊几句老师也更轻松点，然后就正常洗漱了。老师颜值看各人喜好了，但是很照片是真的几乎一致，没过p的成分，这点是加分项。嫩妹大家也知道口活确实很一般需要调教，但老师很听话，会按照你说的做且听从你的一切安排这点是比较好的。等到…
❤3
#南山 #林雪 #1000p ❓ 课表差异点 课表该有的都有，不夸张 😀 优点 高个长腿，有肉但不胖，小c-的天然胸，偏白，态度好很敬业，身材不错很好的炮架，入行感觉得到没多久，年轻嫩姐，属大车，反馈自然，性价比ok 👏 缺点 女上比较虚，小烟味，可能累的原因脸比较苍白没血色，脸上皮肤明显有熬夜的痕迹 📱 出击经历 地点南山科技园，下停车场上楼开门，人照8，跟图1模子像，坐在沙发上，起身来了个大拥抱，很高，我喜欢这种带肉的大车身材，喝了口水就洗澡去了，老师整个过程比较自然不会很生硬。上床后、老师开始正常服务，服务有点小生疏但是很认真。过了一会就我玩弄了一下胸和摸了摸小妹妹感受到很多水后，女上进入，但是女上没几秒老师就累了，能感觉老师很虚，就换我在上，老师属于闭眼轻声呻吟类型，换了几个姿势最后打开窗帘望着写字楼进行了最后的冲击，我觉得值得打卡好的炮架，会返类型 😎 青楼是否认证 已认证 🏅 青楼等级 淑妃 中偏上 …
❤2
#南山 #木子 #1000p ❓ 课表差异点 没啥差异，身高也接近170，属于黄皮但是偏白的 😀 优点 江苏妹子，年轻嫩姐，胸c+天然，168个长腿，随性性格，易高潮，皮肤光滑，臀算大，做爱感觉反馈佳，颜值底子可以但懒不化妆，性价比高！ 👏 缺点 懒，抽烟：纹身看是否能接受，没适应南方天气有点起小点点 📱 出击经历 水友强烈推荐，于是换了个小号咨询老师位置就去了，差点去错教室很尴尬…见面就感觉老师是随性性格，白t里面空档，类似吊钟奶，整个屋子也比较小乱，看得出来老师挺懒的，不爱打理，也没咋化妆，颜值底子是不错的，我不爱闲聊于是立马洗澡了，洗完上床，老师房间很亮很亮不是昏暗房间加分，老师口的挺舒服的没齿感，不管是小豆豆还是还有都挺敏感。老师女上挺有体力，慢慢摇自己再手动控制一下很容易来感觉，加上上下其手很容易高潮。换了3个姿势感觉老师都来了高潮的感觉，属于敏感体质，反馈不像演，明显的生理反应，腰挺起，做爱的反馈比较真实，…
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#南山 #知意 #1300p ❓ 课表差异点 身高168左右，胸c-d之间，正常肤色黄皮 😀 优点 性格大方，能唠嗑，胸有c往上一点，身体特别柔软一字马肯定没毛病，做爱反馈可以，感觉比较喜欢做爱那种，会叫爸爸我要，属于年轻带骚，口活好，皮肤嫩滑 👏 缺点 黄皮，略带点小肚子，年纪不大略显经验，同等价位略贵了点，照片过于惊艳 📱 出击经历 拖青楼群主的福，拿到了优惠出击，按照老师指引如实来到教室。开门略带点小失望，可能看到照片预期太高，照片实在青春美丽，跟第三张照片有点像，大概人照7.5-8。见面老师就感觉到很能聊天性格开朗，老师属于比较慢条斯利的，不着急，正式之前也会调戏下你。洗完澡就上床了，一上床就感觉老师属于那种性爱小野兽，舌头各种骚动，甚至嘴里爸爸也叫个不停，也主动拉你去舔奶子，几乎我就属于被动一方，老师不断猛攻，自己123，换了2个左右姿势就被老师给榨了😂 😎 青楼是否认证 已认证 🏅 青楼等级 淑妃 下 …
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Showing the 12 most recent of 17 posts we hold for @qljb20. 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.
Named by 3 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.
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 9 September 2026 — this entry's latest reading, not the date you are reading this.
“青楼简报” (@qljb20), 10,063 subscribers as measured 9 September 2026. Telegram Register, tgregister.com/channel/qljb20.
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.