【编号】ML1714 【花名】嘟嘟 【车牌】@dudu4848 【地址】成华区 【价格】P 600 元 / Pp 1000 元 【标签】69 600 1000 巨乳 大胸 微胖 丰满 嫩妹 代聊 感觉车 大蟒蛇 舌吻 情绪价值 深喉 女友感 制服 【颜值】8 分 【身材】8 分 【环境】9 分 【服务】9 分 【总评】优点很嫩特别嫩,而且不是精神小妹就像邻家妹妹,长的可爱,服务认真仔细,微胖界的嫩妹天花板了。口的时间很久,会深喉,可以去窗前做爱 ━━━━━━━━ 更多真实测评 · 上百位老师在线 · 打开小程序随时约 → 查看完整资料 / 立即预约(小程序) → 打开小程序看更多老师

Channel
名流车库
@TianFuMingLiuCheKu
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
19,246subscribers
+1,002 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1002281995048 |
|---|---|
| Type | Channel |
| Username | @TianFuMingLiuCheKu |
| 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 | 5 September 2026 |
| Measurements held | 27 |
| Confirmed unchanged | 1 time, most recently 5 September 2026 |
| On Telegram | t.me/TianFuMingLiuCheKu |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 5 Sept 2026, 05:16 | 19,246 | +32 |
| 3 Sept 2026, 08:55 | 19,214 | +41 |
| 2 Sept 2026, 02:38 | 19,173 | +13 |
| 1 Sept 2026, 04:14 | 19,160 | +23 |
| 31 Aug 2026, 03:55 | 19,137 | +55 |
| 30 Aug 2026, 01:34 | 19,082 | +18 |
| 29 Aug 2026, 03:16 | 19,064 | +56 |
| 28 Aug 2026, 02:03 | 19,008 | -44 |
| 26 Aug 2026, 23:58 | 19,052 | +8 |
| 26 Aug 2026, 00:55 | 19,044 | +23 |
| 25 Aug 2026, 01:16 | 19,021 | +41 |
| 23 Aug 2026, 16:38 | 18,980 | +23 |
| 22 Aug 2026, 00:47 | 18,957 | -33 |
| 20 Aug 2026, 19:44 | 18,990 | +39 |
| 19 Aug 2026, 16:32 | 18,951 | +50 |
| 18 Aug 2026, 13:42 | 18,901 | +107 |
| 17 Aug 2026, 10:08 | 18,794 | +69 |
| 15 Aug 2026, 20:14 | 18,725 | +75 |
| 14 Aug 2026, 09:24 | 18,650 | +186 |
| 13 Aug 2026, 00:55 | 18,464 | first reading |
Engagement
154 posts held, back to 5 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 57 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 2.78%
- avg views ÷ 19,246 subscribers
- Avg views / post
- 536
- 143 posts measured
- Reaction rate
- 0.178%
- reactions ÷ views · ER floor
- Posts in window
- 143
- of 154 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 63 of 143 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 2 September 2026 |
|---|---|
| Posts held | 154 (5 August 2026 – 2 September 2026) |
| Views total | 76,637 |
| Reactions total | 66 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 3 Sept 2026, 01:27 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
- 6m 06s
- Average length
- 15s
Measured directly from 25 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
73 reactions across 50 posts, in 4 distinct kinds. The most used accounts for 80.8% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 59 | 80.8% | |
| 👎 | 11 | 15.1% | |
| 💩 | 2 | 2.74% | |
| 👍 | 1 | 1.37% |
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 69 of the 154 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 73 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 154 most recent posts we hold, published 5 August 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
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❤2
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【编号】ML1706 【花名】曲奇 【车牌】@j9_mzi 【地址】武侯区 【价格】p 500 元 / Pp 800 元 【标签】600 少妇 代聊 深喉 毒龙 制服 情绪价值 【颜值】8 分 【身材】8 分 【环境】10 分 【服务】9 分 【总评】推荐给喜欢吃服务,享受型的兄弟去体验,服务非常仔细很舒服,缺点不🐍,服务车! ━━━━━━━━ 更多真实测评 · 上百位老师在线 · 打开小程序随时约 → 查看完整资料 / 立即预约(小程序) → 打开小程序看更多老师
❤2
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❤1
【编号】ML1715 【花名】东门穗穗 【车牌】@suisuiai520 【地址】成华区 【价格】P 400 元 / PP 600 元 【标签】69 400 巨乳 大胸 少妇 自聊 深喉 大蟒蛇 毒龙 情绪价值 感觉控 匈奴人 舌吻 口爆 制服 【颜值】8 分 【身材】9 分 【环境】9 分 【服务】9 分 【总评】老师在这个价位非常值得体验,性价比很高,适合服务控,胸控,身材控体验。 ━━━━━━━━ 更多真实测评 · 上百位老师在线 · 打开小程序随时约 → 查看完整资料 / 立即预约(小程序) → 打开小程序看更多老师
❤2
【编号】ML1712 【花名】芝士 【车牌】@zhishi409 【地址】成华区 【价格】P 500 元 / Pp 900 元 【标签】69 500 贫乳 排骨精 嫩妹 甜妹 萝莉 代聊 感觉车 深喉 敏感车 大蟒蛇 舌吻 制服 情绪价值 女友感 感觉控 符文 【颜值】8 分 【身材】9 分 【环境】9 分 【服务】9 分 【总评】适合嫩妹控,排骨控,娇小控,萝莉控,紧控,感觉控。5米强烈推荐打卡。 ━━━━━━━━ 更多真实测评 · 上百位老师在线 · 打开小程序随时约 → 查看完整资料 / 立即预约(小程序) → 打开小程序看更多老师
【编号】ML1711 【花名】涵涵 【车牌】@hanhan663 【地址】双流区 【价格】P 600 元 / Pp 1000 元 【标签】600 巨乳 丰满 嫩妹 代聊 舌吻 制服 反差 女友感 深喉 【颜值】8 分 【身材】8 分 【环境】9 分 【服务】8 分 【总评】适合喜欢嫩的狼友出击,需要自行引导,不然妹妹不是很放得开 开6还是值得冲的 ━━━━━━━━ 更多真实测评 · 上百位老师在线 · 打开小程序随时约 → 查看完整资料 / 立即预约(小程序) → 打开小程序看更多老师
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👎9
Showing the 12 most recent of 154 posts we hold for @TianFuMingLiuCheKu. 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 7 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.
@LotteryBestBot · 97,7893 posts成都天府名流
@ChengDuTianFuMingLiu · 26,3542 postsLotteryBest抽奖导航
@lotterynav · 170,4732 posts成都百花半套会所
@CD_baihua · 17,1881 post成都柒月女女女女仆mmk私影体验馆
@cdnnnnpmmk · 2,8421 post成都柒月女女女女仆MMK私影恋爱馆
@CDQYMMK · 6,4691 post成都甜魅女仆私人影吧
@cdtmmaid · 4,7621 post全国包养萝莉/处女/学妹(广告频道)
@cpth6 · 191 post成都真🈳商务KTV 酒吧全城安排
@KTV88664 · 111 post🌸蓉凤传🌸
@rongfengzhuan · 1,9371 post成都周周验证精选外围
@zhouzhou028028 · 2,3691 post
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 5 September 2026 — this entry's latest reading, not the date you are reading this.
“名流车库” (@TianFuMingLiuCheKu), 19,246 subscribers as measured 5 September 2026. Telegram Register, tgregister.com/channel/TianFuMingLiuCheKu.
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.