葫芦娃和平精英🎮公益内核9.1更新日志 🌭新增轮胎绘制,血量绘图 🌭新增轮胎追踪,优先攻击可见轮胎 🌭新增巡查预警出,观战预警显示 目前葫芦娃已适配PUBG4.5🎮最新四服,和平精英🎮,无畏契约🎮三游戏,网页雷达共享,软件雷达共享都已公益免费使用,卡密随便输入 主频道: @appletzpd0 ✍️光头强频道: @gtqnb0000 🎉葫芦娃频道 :@HLWNHNBB 👍万能搜索 @Tab99811111111
❤14👍6👨💻1

Channel
@HLWNHNBB
On this record: Topic · Observations · Growth · Engagement · Reactions · Posts · Citations · Cite this entry
10,155subscribers
+108 since we began measuring on 11 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1002597307391 |
|---|---|
| Type | Channel |
| Username | @HLWNHNBB |
| Created | Between 1 March 2025 and 31 July 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 11 August 2026 |
| Last confirmed live | 12 August 2026 |
| Measurements held | 2 |
| Confirmed unchanged | 1 time, most recently 12 August 2026 |
| On Telegram | t.me/HLWNHNBB |
Gaming — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 11 August 2026 and assigned it the closest of 31 fixed categories, at 43% 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.
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
8,820 average views per post against 10,155 subscribers — an engagement rate of 86.8%. Across the 1,871 registered channels in the same cohort — 10,003–31,611 subscribers, posting mainly in Chinese — the middle half sit between 1.94% and 11.5%, with a median of 4.82%.
| Window | 30 days (13 July 2026 – 12 August 2026) |
|---|---|
| Posts measured | 14 of 14 published in the window (0 exact, 14 rounded by Telegram) |
| Views totalled | 123,470 |
| Mature posts only | 86.8% over 14 posts read at least 24h after publication |
| Subscribers | 10,155 measured 12 August 2026 |
| Cohort | b10000:zho · 1,871 channels · p10 0.566% · p25 1.94% · p50 4.82% · p75 11.5% · p90 24.9% |
| Position in cohort | 99.144th percentile · 18.0× the cohort median |
| Uncertainty | ±0.289% of the figure, from Telegram’s rounding |
| Post language | Chinese · 100.0%of the window’s posts |
When this is recorded. A channel is listed here only when its engagement rate sits at or above the 99th percentile of its cohort and is at least 3× away from that cohort’s median — above it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal.A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the key err_high, last confirmed 12 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 12 Aug 2026, 11:36 | 10,155 | +108 |
| 11 Aug 2026, 19:46 | 10,047 | first reading |
17 posts held, back to 7 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 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.
| Window | Rolling 30 days · latest post in window 11 August 2026 |
|---|---|
| Posts held | 17 (7 July 2026 – 11 August 2026) |
| Views total | 123,470 |
| Reactions total | 317 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Aug 2026, 07:50 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.
437 reactions across 17 posts, in 9 distinct kinds. The most used accounts for 61.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 268 | 61.3% | |
| 👍 | 111 | 25.4% | |
| 🫡 | 48 | 11.0% | |
| 🎉 | 3 | 0.686% | |
| 👎 | 2 | 0.458% | |
| 🔥 | 2 | 0.458% | |
| 👨💻 | 1 | 0.229% | |
| 😍 | 1 | 0.229% | |
| 🤯 | 1 | 0.229% |
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 17 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 437reactions 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 7 July 2026 to 11 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.
葫芦娃和平精英🎮公益内核9.1更新日志 🌭新增轮胎绘制,血量绘图 🌭新增轮胎追踪,优先攻击可见轮胎 🌭新增巡查预警出,观战预警显示 目前葫芦娃已适配PUBG4.5🎮最新四服,和平精英🎮,无畏契约🎮三游戏,网页雷达共享,软件雷达共享都已公益免费使用,卡密随便输入 主频道: @appletzpd0 ✍️光头强频道: @gtqnb0000 🎉葫芦娃频道 :@HLWNHNBB 👍万能搜索 @Tab99811111111
❤14👍6👨💻1
AI模型识别自瞄,和平的模型是找朋友。用1万多张图片训练的识别度很高,隔着200多米都能识别出来 三角洲跟瓦罗兰特的人物模型是用的开源的,我没测试 用开源源码改的我自己优化了一下,玩着还行,肯定比不上内核自瞄,但是没root的玩家还是可以玩一下,自己调好了还是挺准的
👍11❤9🔥1
葫芦娃yolo免root模型AI吸附自瞄 支持和平精英🎮,三角洲❤️,PUBG四服🎮,无畏契约🎮四款手游 有root权限用户直接给root就行,没有root的需要安装shizuku配合使用 和平精英跟PUBG模型可以直接通用 有root直接用陀螺仪自瞄,触摸有些机型不适配,多尝试一下它有好几种触摸模式 自瞄参数需要你们自己研究调一下,这个比较麻烦,大家自己讨论吧 本模型AI自瞄识别来自git开源网站二改优化来的,永久公益免费,禁止任何人倒卖盈利 主频道: @appletzpd0 ✍️光头强频道: @gtqnb0000 🎉葫芦娃频道 :@HLWNHNBB 👍万能搜索 @Tab99811111111
❤13👍8
葫芦娃永久公益内核更新日志 🎮无畏契约 适配新赛季 🎮和平精英 增加地铁轩辕boos绘制 密钥使用单独文本颜色和字体大小 🎮PUBG四服 修复最新闪框解密 主频道: @appletzpd0 ✍️光头强频道: @gtqnb0000 🎉葫芦娃频道 :@HLWNHNBB 👍万能搜索 @Tab99811111111
❤35👍8🎉3🤯1😍1
#葫芦二娃 葫芦娃和平精英🎮公益内核8.7更新日志 🌭新增突击兵,特种兵,指挥官等密钥解密功能 🌭增加躲猫猫绘制 🌭修复内鬼绘制 主频道: @appletzpd0 ✍️光头强频道: @gtqnb0000 🎉葫芦娃频道 :@HLWNHNBB 👍万能搜索 @Tab99811111111
❤26
卧槽和平加密真恶心,游戏直接锁60帧🤡 我说怎么一堆人说小烧鸡卡呢,之前我账号没加密,打的贼丝滑,今天死人和平给我下发个加密。都快卡成小米8了 账号被加密了就别开算法解密硬玩了,一点游戏体验都没有,直接刷机换个号玩得了
👍21❤4
葫芦娃和平精英🎮公益内核8.6更新日志 🌭倒地绘制变色增加单独的开关 🌭增加自动保存上次卡密功能 葫芦娃🎮PUBG内核更新日志 🌭修复最新闪框加密 主频道: @appletzpd0 ✍️光头强频道: @gtqnb0000 🎉葫芦娃频道 :@HLWNHNBB 👍万能搜索 @Tab99811111111
❤28
#葫芦二娃 HLW无畏契约更新 新增无畏契约闪框解密 原理缓存正常帧坐标 过滤异常坐标,完全不动内存, 缺点:远处人物会被过滤不显示 主频道: @appletzpd0 ✍️光头强频道: @gtqnb0000 🎉葫芦娃频道 :@HLWNHNBB 👍万能搜索 @Tab99811111111
❤11👍2
#葫芦二娃 葫芦娃和平精英🎮公益内核8.5更新日志 🌭修复APP共享雷达服务器失效 🌭新增水陆两系飞机显示 🌭修复妹控开镜自瞄锁人 🌭修复敌人倒地颜色 🌭修复火山地图的空投和飞机不显示 🌭和平密钥匙颜色优化,字体增大 🌭名字大小变成可调节 🌭更新和平载具移动变色 主频道: @appletzpd0 ✍️光头强频道: @gtqnb0000 🎉葫芦娃频道 :@HLWNHNBB 👍万能搜索 @Tab99811111111
❤14👍4
#葫芦二娃 🌭修复用户开启闪框解密后,射线雷达绘制异常的bug 🌭新增主题海岛飞船显示 🌭新增主题海岛空投显示 目前葫芦娃已适配PUBG4.5🎮最新四服,和平精英🎮,无畏契约🎮三游戏,网页雷达共享,软件雷达共享都已公益免费使用,卡密随便输入 主频道: @appletzpd0 ✍️光头强频道: @gtqnb0000 🎉葫芦娃频道 :@HLWNHNBB
❤22👍2
#葫芦二娃
❤20👍2
#葫芦二娃 简介: 更新时间:2026-07-19 07:13:28
❤9👍9
Showing the 12 most recent of 17 posts we hold for @HLWNHNBB. 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 — 48,037 of 1,151,006entries 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.
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.
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 12 August 2026 — this entry's latest reading, not the date you are reading this.
“葫芦娃公益小家庭” (@HLWNHNBB), 10,155 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/HLWNHNBB.
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.