📊 0条车评,综合评分 好评 0% |人照 |服务 中评 0% |颜值 |态度 差评 0% |身材 |环境 艺名 玫瑰 地址 盘龙区 ☎️ @hshuwhuqi 标签导航 #颜控 #包夜 #不限次 #毒龙 #服务系 #7p 身材控 写报告 @Kmcgdibot 大群
❤2

Channel
@kunmingziyuan11
On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Cite this entry
12,108subscribers
-51 since we began measuring on 19 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1002281357464 |
|---|---|
| Type | Channel |
| Username | @kunmingziyuan11 |
| Created | Between 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 19 August 2026 |
| Last confirmed live | 15 September 2026 |
| Measurements held | 22 |
| Confirmed unchanged | 1 time, most recently 15 September 2026 |
| On Telegram | t.me/kunmingziyuan11 |
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 11 September 2026 and assigned it the closest of 31 fixed categories, at 84% 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 |
|---|---|---|
| 15 Sept 2026, 06:40 | 12,108 | -23 |
| 13 Sept 2026, 15:55 | 12,131 | -166 |
| 11 Sept 2026, 18:57 | 12,297 | -58 |
| 9 Sept 2026, 09:40 | 12,355 | -68 |
| 6 Sept 2026, 05:38 | 12,423 | -17 |
| 4 Sept 2026, 01:17 | 12,440 | -39 |
| 2 Sept 2026, 12:52 | 12,479 | -8 |
| 1 Sept 2026, 14:43 | 12,487 | -2 |
| 31 Aug 2026, 13:13 | 12,489 | +7 |
| 30 Aug 2026, 16:14 | 12,482 | +33 |
| 29 Aug 2026, 14:34 | 12,449 | +1 |
| 28 Aug 2026, 13:36 | 12,448 | +20 |
| 27 Aug 2026, 12:24 | 12,428 | +38 |
| 26 Aug 2026, 13:36 | 12,390 | +6 |
| 25 Aug 2026, 10:16 | 12,384 | +22 |
| 24 Aug 2026, 10:45 | 12,362 | +54 |
| 22 Aug 2026, 21:26 | 12,308 | +57 |
| 21 Aug 2026, 13:14 | 12,251 | +23 |
| 20 Aug 2026, 13:27 | 12,228 | +41 |
| 19 Aug 2026, 15:41 | 12,187 | first reading |
9 posts held, back to 23 June 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 26 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 3 of 5 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 24 August 2026 |
|---|---|
| Posts held | 9 (23 June 2026 – 24 August 2026) |
| Views total | 4,186 |
| Reactions total | 5 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 2 Sept 2026, 21:42 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.
13 reactions across 7 posts, in 3 distinct kinds. The most used accounts for 76.9% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 10 | 76.9% | |
| 👍 | 2 | 15.4% | |
| 😁 | 1 | 7.69% |
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 9 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 13 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 9 most recent posts we hold, published 23 June 2026 to 24 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.
📊 0条车评,综合评分 好评 0% |人照 |服务 中评 0% |颜值 |态度 差评 0% |身材 |环境 艺名 玫瑰 地址 盘龙区 ☎️ @hshuwhuqi 标签导航 #颜控 #包夜 #不限次 #毒龙 #服务系 #7p 身材控 写报告 @Kmcgdibot 大群
❤2
📊 0条车评,综合评分 好评 0% |人照 |服务 中评 0% |颜值 |态度 差评 0% |身材 |环境 艺名 雅迪 地址 西山区 ☎️ @yd19972 标签导航 #包夜 #鸳鸯浴 #六九 #5p #9pp #上门 #服务系 写报告 @Kmcgdibot 大群
😁1
📊 0条车评,综合评分 好评 0% |人照 |服务 中评 0% |颜值 |态度 差评 0% |身材 |环境 艺名 言希 地址 官渡区 ☎️ @yan_520 标签导航 #嫩妹 #7p #13pp #长发 #按摩 #服务系 写报告 @Kmcgdibot 大群
📊 0条车评,综合评分 好评 0% |人照 |服务 中评 0% |颜值 |态度 差评 0% |身材 |环境 艺名 浪浪 地址 盘龙区 ☎️ @langG520 标签导航 #不限次 #长发 #毒龙 #包夜 #上门 #水中箫 #六九 写报告 @Kmcgdibot 大群
👍2
📊 0条车评,综合评分 好评 0% |人照 |服务 中评 0% |颜值 |态度 差评 0% |身材 |环境 艺名 柒柒 地址 官渡区 ☎️ @qiqi681688 标签导航 #嫩妹 #短发 #毒龙 #舌吻 #无套口 #观音座莲 #6p #11pp #包夜 #上门 写报告 @Kmcgdibot 大群
📊 0条车评,综合评分 好评 0% |人照 |服务 中评 0% |颜值 |态度 差评 0% |身材 |环境 艺名 苍老师 地址 官渡区 ☎️ @cls16cls 标签导航 #长发 #服务系 #毒龙 #艳舞 #高山流水 #倒挂金钩 #花式调情 #六九 #海底捞月 #深喉 #日式操口 #英式侧口 #韩式站口 #15pp #8p #包夜 写报告 @Kmcgdibot 大群 https://t.me/kunmingchaguan
❤2
📊 32条车评,综合评分9.72 好评 100% |人照 9.55 |服务 9.94 中评 0% |颜值 9.7 |态度 9.95 差评 0% |身材 9.56 |环境 9.59 艺名: #安迪 联系方式: @andi6689 标签导航:#昆明 #西山 #御姐 #6P #9PP #舌吻 #六九 #足交 #陪浴 #水中萧 #半套 #双飞 #不限次 #SM #毒龙 #口爆 #包夜 管理员 @kunmingCGbot
❤1
📊 10条车评,综合评分9.33 好评 100% |人照 8.8 |服务 9.75 中评 0% |颜值 9.08 |态度 10 差评 0% |身材 9.06 |环境 9.31 艺名 #婉儿 联系老师 @waner537 地址 西山万达 管理员 @kunmingCGbot
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📊 34条车评,综合评分9.75 好评 97.1% |人照 9.56 |服务 10 中评 2.9% |颜值 9.63 |态度 10 差评 0% |身材 9.64 |环境 9.64 艺名 #糖糖 联系老师 @tang895 标签导航 #昆明 #西山 #上门 #万达广场 #服务控 #声音控 #御姐 #6P #舌吻 #六九 #足交 #陪浴 #水中萧 #半套 #双飞 #不限次 #车震 #陪玩 #SM #毒龙 #口爆 #包夜 管理员 @kunmingCGbot
❤3
Showing the 9 most recent of 9 posts we hold for @kunmingziyuan11. 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.
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 15 September 2026 — this entry's latest reading, not the date you are reading this.
“昆明茶馆专榜” (@kunmingziyuan11), 12,108 subscribers as measured 15 September 2026. Telegram Register, tgregister.com/channel/kunmingziyuan11.
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.