Channel
@zheli_5
On this record: Topic · Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
1subscribers
+0 since we began measuring on 8 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1004343273962 |
|---|---|
| Type | Channel |
| Username | @zheli_5 |
| Created | Between 1 June 2026 and 2 August 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 14 August 2026 |
| Last confirmed live | 2 October 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 2 October 2026 |
| On Telegram | t.me/zheli_5 |
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 3 October 2026 and assigned it the closest of 31 fixed categories, at 67% 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 |
|---|---|---|
| 2 Oct 2026, 20:41 | 1 | -1 |
| 25 Aug 2026, 04:15 | 2 | +1 |
| 14 Aug 2026, 15:15 | 1 | no change |
| 8 Aug 2026, 10:56 | 1 | first reading |
6 posts held, back to 2 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 1 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 6 posts for this entry, the most recent from 2 August 2026. An engagement rate over an empty window would be a number about nothing.
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.
沪商圈🍾专注上海商务资源😛 内容： 提供高质量女士出席商务应酬、伴游、伴客、伴酒、接待、约会等。 价格： 三起资源3000（1小时）丨8000（22:00-8:00)丨15000（24小时） 五起资源5000（1小时）丨15000（22:00-8:00）丨30000（24小时） W起资源10000（1小时）丨 30000（22:00-8:00）丨45000（24小时） 来源： 学生兼职、社会素人、媒体网红、职业外围、健身教练、航司空姐、医院护士、cos萝莉、企业白领等。 年龄： 18岁-50岁 流程： 99-888门槛入圈↙️ 提供具体需求↙️ 预约时间&见面地点↙️ 见面后满意需先付款后服务↙️ 付款后即计算服务时间🕦 服务时间内皆言听计从为所欲为🔞 联系我们： @JsDzz @hushang8 https://t.me/DDwwkfbot 一线分类资源： 上海3k 上海5k …
#杭州 苏微微 #校 媛媛 ❏ age /21 ʜɪɢʜᴛ/ 168ᴄᴍ ❏ ᴡᴇɪɢʜ/ 45KG ᴄᴜᴘ/ D ❏ 全身雪白 三点粉 ❏ 江南女孩 温婉如玉 初恋女友 ❏ 新人第一次下💦 一个导不认识 ❏ 🉑69 🉑舌吻 🉑车震 🉑✌🏻 ❏ 全身无整 无纹身 皮肤超白嫩 ❏ 双商高 乖巧听话 不催不事 ❏ 主动配合100% ❏ 少女热情超级配合，不催不事 #萧山区 #硬五
#杭州 苏微微 #猩 小熊 传媒学生短暂兼职 随时上岸 真实07年（可看证）19岁 净身高176cm，体重48kg 胸围c 高白醇天花板 ~~~~~~~~~ 天然妈生脸🈚️整容 常年瑜伽戶外運動 愛好｜美妝 穿搭 健身 喜胖勿扰 高挑黑长直大长腿 全身雪白紧致 冷白皮无滤镜 有腹肌 无纹身 ✨S身材 甜美欲纯系 纯兼职 ✦ 一字肩 𝔸𝟜 腰 筷子腿 马甲线 ✦ 蜜桃臀 腰上没一点赘肉 💞 #上城区 #硬五
#杭州 苏微微 #奶 洋气网红🦜W 高情商 会聊天 懂配合 真实03 性格温柔 皮肤雪白细腻 #萧山区 #硬五
#杭州 苏微微 #尼 网红主播 学生偶尔兼职 风格多变 充满情趣 五官超立体 天然白虎 三点粉 馒头一线天 有30万粉丝 温柔如女友 爱撒娇 巨嗲👄 年龄/𝑎𝑔𝑒: 05年 身高/ℎ𝑡:168 罩杯/𝑐𝑢𝑝:E 体重/𝑤𝑡: 95斤 经常健身 有蜜桃臀马甲线 逆天腰臀比 幼态魅惑脸蛋 肌肤光滑细腻 性格超级好 可素颜见课 自带情趣高跟 腿直且细 但是没有逆天大长腿 要逆天大长腿的哥哥请转身 高端私密gzs #萧山区 #硬五
#杭州 苏微微 #令 蜜桃 杭州175F 真·全能选手 身高：175 胸围：天然大F 产地：温州 天然骨子里的骚浪贱 <给钱什么都可以> 🉑接受客人指派任务，诸如户外露出，勾引路人司机等等。🉑轻度中度重度sm，🉑3t，🉑毒🐉。 各种专业sm道具，玩具，一些列情趣样样俱全 🐍技惊人，舔功一流，🉑口💥吞精 完全开放型选手，欢迎品鉴体验！ #上城区 #硬五 #SM #三通
Showing the 6 most recent of 6 posts we hold for @zheli_5. 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.
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.
Named by 8 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 2 October 2026 — this entry's latest reading, not the date you are reading this.
“浙里约丨杭州5k” (@zheli_5), 1 subscribers as measured 2 October 2026. Telegram Register, tgregister.com/channel/zheli_5.
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.