Travel — 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 12 September 2026 and assigned it the closest of 31 fixed categories, at 52% 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 the other topics.
Growth
25 measurements spanning 91 days, net -173. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 6,399–6,624 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 25
Measured (UTC)
Subscribers
Change
6 Nov 2026, 06:18
6,425
-5
3 Nov 2026, 06:38
6,430
-2
31 Oct 2026, 09:08
6,432
+4
28 Oct 2026, 05:30
6,428
-7
25 Oct 2026, 01:50
6,435
-5
21 Oct 2026, 20:38
6,440
-21
18 Oct 2026, 14:56
6,461
-4
15 Oct 2026, 07:59
6,465
+1
11 Oct 2026, 20:21
6,464
-24
5 Oct 2026, 08:58
6,488
-6
27 Sept 2026, 11:59
6,494
-1
18 Sept 2026, 11:55
6,495
-9
13 Sept 2026, 22:39
6,504
-8
9 Sept 2026, 23:58
6,512
-6
4 Sept 2026, 21:22
6,518
-4
1 Sept 2026, 12:14
6,522
-11
29 Aug 2026, 15:26
6,533
-7
26 Aug 2026, 13:52
6,540
-11
23 Aug 2026, 16:16
6,551
-2
19 Aug 2026, 23:23
6,553
first reading
Engagement
48 posts held, back to 24 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 13 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
13.8%
avg views ÷ 6,425 subscribers
Avg views / post
889
23 posts measured
Reaction rate
7.88%
reactions ÷ views · ER floor
Posts in window
23
of 48 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.
What these figures were computed from
Window
Rolling 30 days · latest post in window 5 November 2026
Posts held
48 (24 July 2026 – 5 November 2026)
Views total
20,454
Reactions total
1,612
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
6 Nov 2026, 02:07 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
7m 34s
Average length
1m 16s
Measured directly from 6 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
3,542 reactions across 47 posts, in 17 distinct kinds. The most used accounts for 34.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🤣
1,218
34.4%
😁
683
19.3%
❤🔥
602
17.0%
🔥
461
13.0%
🍾
197
5.56%
👏
176
4.97%
💯
39
1.10%
💔
33
0.932%
🙏
25
0.706%
🕊
20
0.565%
👀
19
0.536%
🤝
15
0.423%
😭
13
0.367%
😨
11
0.311%
🤗
11
0.311%
⚡
10
0.282%
✍
9
0.254%
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 47 of the 48 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 3,542 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 48 most recent posts we hold, published 24 July 2026 to 5 November 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.
Telegram Stars
Stars received
1
across the posts below
Posts paid on
1
of 47 we hold a reading for · 2%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @let_9. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 48 most recent posts we hold for this entry, published 24 July 2026 to 5 November 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
Recent posts
Telegram’s own ‘edited’ marker: 6 of 23 posts held from the last 30 days (26.1%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
Помните строчки про Ивана Сусанина, я вроде бы даже учила их наизусть:
Куда ты ведешь нас?.. не видно ни зги! —
Сусанину с сердцем вскричали враги: —
Мы вязнем и тонем в сугробинах снега;
Нам, знать, не добраться с тобой до ночлега.
Ты сбился, брат, верно, нарочно с пути;
Но тем Михаила тебе не спасти
Что тут правда, а что — художественный вымысел, мы рассказываем в новом фильме про Кострому.
А ещё чем русалки отли…
🎬 Премьера! Колыбель Романовых, родина Сусанина, деда Мазая и Снегурочки — все это Кострома. А мы сняли про древний город фильм и покажем его сегодня в 20.00 на канале «365 дней ТВ».
Мы неслучайно приурочили премьеру этого фильма к Дню народного единства. В этот день мы отмечаем освобождение Москвы от польских захватчиков. Однако именно в Костроме произошло событие, завершившее Смутное время, — призвание на царство…
Приехали в Новгород, где не были месяц-полтора. Гера берет из стеклянной колбочки предпоследнюю капсулу кофе.
Я (тревожно): — А больше нет?
Гера (торжественно):
— Конечно же, есть!
Застывает в позе античного бога, потом оттаивает и достает из ящичка упаковку капсул, купленную в прошлый приезд.
— Кто тут великолепный и запасливый муж? А? Вот! (Спохватывается) Но ты заслужила, заслужила!
10 мая 1746 императрица Елизавета Петровна издала странное, на первый взгляд, распоряжение: «… в сад никого не пускать и поставить караул; ежели же кто силой и упрямством пойдет, в таких упрямцев стрелять из ружья горохом».
Речь шла о садах Царского Села, в которых высаживали редкие деревья, устанавливали статуи и строили диковинные павильоны. Десятки лет спустя царскосельские летописцы будут называть один из них «ч…
Сын мой — тролль ещё тот. В ответ показал видео⬆️
Потом сидит тихонько, суп ест.
— Вообще-то я виню тебя только в одном...
Пауза.
Пауза.
ПАУЗА.
Хлюпанье супом.
— Суп охрененный, конечно.
А нужен ли ему психолог? По-моему, он все уже умеет 😏
Сын мой, кстати, ходит к психологу. Поначалу договорились: все, что они там обсуждают, — тайная тайна. Но кто помешает матери задать невинный вопрос?
«А вы уже дошли до того, что во всем виноваты родители?»
Пока я тут плачусь на возраст и публикую грустные фотки, две прекрасные феи Ирина Амосова и Мария Дьячкова завели канал про адаптированные для жизни биохакерские штучки — Home Biohackerus.
На самом деле, девушки — построили косметическую компанию с оборотом свыше 2 млрд руб, их продукция продается в 15 странах мира. Но ни один крем не сделает нас молодыми, если внутри — хаос, недосып и стресс.
Поэтому девушки нырн…
Возила сЫночку в аутлет. Купили ему всякого. Но пришлось, конечно, походить, померить, пострадать.
Едем назад. Говорит: «Я до конца дня буду варёный».
Предупреждает то есть, чтоб не приставали — «а кто у нас тут такой грустный?!»
Хотела бы возмутиться, но очень его понимаю. А ведь ещё бывает так, что ходишь 5 часов голодная, потная вся, ноги уже стёрла. В итоге насмотришься в примерочных, какая ты старая, толстая …
Едем вчера с Герой домой и я сокрушаюсь, что молодые сотрудники называют меня по имени-отчеству. Говорю: «Как это все случилось?» И тут в окне справа проплывает вывеска ⬇️
В ночи смотрела, какие нынче дорогие и натуральные делают искусственные растения. Какая-то метровая олива в горшке стоит сотню тысяч.
Но всем этим искусственным премиум-деревьям далеко до царских букетов.
Вчера я делилась ссылкой на наш фильм о Китайском зале (Екатерининский дворец в Царском Селе). Со времен Екатерины II в Китайском зале вдоль стен на консольных столах были выставлены диковинные предметы — редкие в…
Как создать шедевральный интерьер? Поискать хорошенечко, что там у вас лежит в кладовке!
В кладовых Большого Царскосельского дворца, к примеру, хранились подарки китайского императора — деревянные лаковые ширмы. С каждой стороны на них был нанесен рисунок: пейзаж, узор или бытовая сцена. Когда Растрелли переделывал дворец для Елизаветы Петровны, он решил распилить ширмы вдоль по всей высоте. Получились деревянные ла…
❤🔥37🔥28🍾8👏3⚡2
Showing the 12 most recent of 48 posts we hold for @let_9. 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
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.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
Хьюстон, у нас проблемы @we_have_problems · 20,220 Telegram ranks this channel #9 of 83 here — alongside 82 others — read 27 September 2026
Обратная сторона Л. @semikolennyh · 18,748 Telegram ranks this channel #44 of 87 here — alongside 86 others — read 4 October 2026
Максимально наша @maximalno_nasha · 25,486 Telegram ranks this channel #52 of 87 here — alongside 86 others — read 14 September 2026
БЕЗУДЕРЖНОЕ ВЕСЕЛЬЕ @bezuderjnoe_veselie · 33,349 Telegram ranks this channel #52 of 70 here — alongside 69 others — read 3 September 2026
Женщина и прочие неприятности @conflict_in · 49,694 Telegram ranks this channel #61 of 86 here — alongside 85 others — read 25 August 2026
Мамыкина явилась @onwritingwell · 23,416 Telegram ranks this channel #65 of 88 here — alongside 87 others — read 18 September 2026
Барышня шутить изволит @baryshnya_shutit · 44,748 Telegram ranks this channel #82 of 84 here — alongside 83 others — read 27 August 2026
This channel appears in 7 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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 6 November 2026 — this
entry's latest reading, not the date you are reading this.
“Мам, я на съемках” (@let_9), 6,425 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/let_9.
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.