Technology — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 42% 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
115 measurements spanning 97 days, net -228. 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 15,623–15,919 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 115
Measured (UTC)
Subscribers
Change
11 Nov 2026, 06:59
15,657
-5
9 Nov 2026, 21:41
15,662
-7
9 Nov 2026, 12:15
15,669
-2
8 Nov 2026, 14:34
15,671
-1
8 Nov 2026, 06:55
15,672
-2
7 Nov 2026, 06:38
15,674
+1
5 Nov 2026, 00:17
15,673
no change
4 Nov 2026, 05:11
15,673
-1
4 Nov 2026, 02:58
15,674
-3
3 Nov 2026, 03:40
15,677
no change
3 Nov 2026, 02:09
15,677
-4
2 Nov 2026, 00:05
15,681
-1
1 Nov 2026, 01:26
15,682
+1
31 Oct 2026, 22:06
15,681
+1
31 Oct 2026, 00:19
15,680
-2
30 Oct 2026, 18:56
15,682
-4
30 Oct 2026, 02:00
15,686
-5
29 Oct 2026, 17:46
15,691
-2
29 Oct 2026, 02:10
15,693
-1
28 Oct 2026, 21:18
15,694
first reading
Engagement
44 posts held, back to 6 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 73 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
22.2%
avg views ÷ 15,657 subscribers
Avg views / post
3,480
4 posts measured
Reaction rate
0.287%
reactions ÷ views · ER floor
Posts in window
4
of 44 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 1 November 2026
Posts held
44 (6 July 2026 – 1 November 2026)
Views total
13,920
Reactions total
40
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
11 Nov 2026, 06:44 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
3m 35s
Average length
24s
Measured directly from 9 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
348 reactions across 42 posts, in 10 distinct kinds. The most used accounts for 30.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
106
30.5%
👍
90
25.9%
🔥
61
17.5%
😁
37
10.6%
💩
30
8.62%
👏
15
4.31%
👎
6
1.72%
👌
1
0.287%
😎
1
0.287%
🤯
1
0.287%
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 43 of the 44 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 348 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 44 most recent posts we hold, published 6 July 2026 to 1 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
10
across the posts below
Posts paid on
1
of 44 we hold a reading for · 2%
Most on one post
10
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @grigor. 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 44 most recent posts we hold for this entry, published 6 July 2026 to 1 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: 0 of 4 posts held from the last 30 days (0%) 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).
У Ютуба через три года залетела ветка в Тредс.
Все пишут и шутят про то, что три года ведешь, потом попадаешь в рекомендации, про 4 рекламы подряд, короче. Как сказал один комментатор «напихали на всех языках мира»
Но за этим забавно наблюдать)
Он красиво молчал, а потом вы даете ему текст.
И получается «у нее преждевременные, началась родильная деятельность».
В нейросетевых видео человек может стоять под дождём, смотреть на горящий город и выглядеть на бюджет небольшой европейской страны.
Потом он открывает рот.
И выясняется, что вместо «Привет, дорогая как дела» он говорит «Привит Олег, как Дима».
С русской речью в ИИ-видео (особенно в Seedance 2.5) е…
Как Якудза нашла мне работу?
Я сделал ролик про Якудзу и получил заказ из Италии на криминальный интернет-сериал.
До чего приятно, когда люди понимают друг друга через культурный контекст. Только вдумайтесь. Армянин из России сделал что-то про Японию и нашел общий (английский) язык с итальянцем. Посмотрим, что из этого выйдет.
Заодно ролик набрал больше 140 тысяч просмотров и привёл 2500 подписчиков в запрещённой …
«Сделайте ещё десять вариантов». Как ИИ меняет отношения с клиентом
На прошлой неделе отправил клиенту двенадцать вариантов ключевого визуала. Через час пришёл ответ: «Классно. А можно ещё десять?»
Можно. В этом и проблема. И дело не в том, что нас снова после двенадцати вариантов отправили работать. Проблема в том, что перебирать можно бесконечно.
Раньше вариант стоил денег. Съёмочный день, фотограф, ретушёр, илл…
На Mindbox Конференции маркетологов будут учить вайбкодингу. Целый день 24 октября — вебинары и воркшопы от Mindbox и школы Вани Замесина.
Автор Advanced JTBD покажет, как в одиночку собрать конвейер по проверке гипотез. Без дизайнера, аналитика и разработчиков.
А 23 октября — доклады и дискуссии: 40+ спикеров, 27 докладов и воркшопов о CRM-маркетинге и рекламе. Часть из них тоже про ИИ и ML. Например:
— аптеки «В…
В этом концепте Lost Cherry флакона нет вообще.
Есть вишня в руках. Сок на коже. Бордовые ногти. Фрукт рассказывает про аромат, крупные планы — про влажность и фактуру.
Если свойство нельзя показать напрямую, переведите его в действие. Сладость — раздавленная спелая ягода. Вязкость — сок, который стекает медленно.
Сначала ощущение. Потом жест, по которому его узнают.
Флакон зритель дорисует сам.
S04 E22 1️⃣ Gri…
Как стоило бы проверять собственный уровень?
Хороший способ проверить свой уровень — взять скучную задачу. Например, письмо клиентам о том, что с первого числа цены вырастут на десять процентов.
Кажется, что это на полчаса.
Цифра почему-то уехала в третий абзац. Причина повышения звучит как оправдание. В тексте трижды встречается «к сожалению». Непонятно, что клиенту делать дальше.
И второй список, с компромиссам…
На сиденье огромное ведро KFC. А реклама — Jim Beam.
В моём spec-ролике героиня разбивает стекло, тянется мимо еды и берёт бутылку. Упаковка рядом крупнее и ярче. Неважно. Главным продукт делает её выбор.
Придумайте для своего товара такую же сцену. Что лежит рядом? К чему тянется рука? Что остаётся?
Так у продукта появляется причина быть в кадре.
А курица так и остаётся на сиденье.
S04 E20 1️⃣ Grigòr, the Crea…
Про кейсы, которые не получается повторить
Кейс на конференции: «Как мы увеличили продажи в три раза за месяц». Механика понятная, слайды красивые. Повторяешь один в один. Никакого результата.
Кажется, у них какой-то секрет.
Но вспомните свой кейс. Даже свой прям один в один повторить не получится.
Секрета нет. Есть кусок истории, который показали.
Кейс начинается поздно. Там уже есть узнаваемый бренд, база клие…
В ролике с самураем кроссовок лучше всего продают кадры, где самурая нет.
Общий план задаёт образ. Потом макро: кожа, плетение шнурков, маркировка. Потом шаг, и вещь снова в движении.
Раскадровка для любого товара: герой целиком → материал → деталь конструкции → маркировка → вещь в деле.
У каждого кадра своя работа, и сразу ясно, что готовить до анимации.
S04 E18 1️⃣ Grigòr, the Creator
Хочу «дорогую» картинку, говорили они
И пишут в промпте: cinematic, luxury, premium, 8k, award-winning.
Флакон блестит. Фон светится. По мрамору текут отражения. Сзади идёт дым. Камера летит по дуге. Вокруг парят золотые частицы.
Это не дорого, это слишком перебор.
В кадре всё одновременно пытается понравиться. Как ученики в классе, которые одновременно пытаются ответить на вопрос.
Новый промпт тут не поможет. П…
👍5
Showing the 12 most recent of 44 posts we hold for @grigor. 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.
Posts recorded as deleted after publishing
We recorded 1 post on @grigor as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
31 August 2026
Most recent seen missing
31 August 2026
Median time before seen missing
10 days
Seen missing in the last 30 days
0
Mentions
Named by 9 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.
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.
В школе этому не учат | Бизнес & Digital @delaumoney · 53,316 Telegram ranks this channel #5 of 86 here — alongside 85 others — read 24 August 2026
Психология Маркетинга @marketpsy · 172,106 Telegram ranks this channel #24 of 98 here — alongside 97 others — read 12 August 2026
Саша Чижов @blogsmm · 38,235 Telegram ranks this channel #26 of 97 here — alongside 96 others — read 31 August 2026
Карты, тексты, два ствола @remingtonist · 26,869 Telegram ranks this channel #29 of 95 here — alongside 94 others — read 11 September 2026
SMM с Дамиром Халиловым @damirkhalilov · 23,103 Telegram ranks this channel #34 of 91 here — alongside 90 others — read 18 September 2026
Текст в тексте @textvtexte · 22,083 Telegram ranks this channel #39 of 87 here — alongside 86 others — read 21 September 2026
Корнеев | Первый Маркетинговый @pervmarketing · 129,017 Telegram ranks this channel #39 of 98 here — alongside 97 others — read 13 August 2026
Цепляющий контент @smm_eng · 22,072 Telegram ranks this channel #43 of 96 here — alongside 95 others — read 20 September 2026
99 франков. Маркетинг @marketolog_marketing · 80,677 Telegram ranks this channel #51 of 95 here — alongside 94 others — read 18 August 2026
Полезный Парфун @ParfunA · 20,653 Telegram ranks this channel #54 of 99 here — alongside 98 others — read 22 September 2026
Маркетинг / Диджитал @marketingj · 20,783 Telegram ranks this channel #54 of 98 here — alongside 97 others — read 20 September 2026
Слава КРАСАВА @smmmarketolog · 18,982 Telegram ranks this channel #72 of 89 here — alongside 88 others — read 1 October 2026
This channel appears in 12 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 11 November 2026 — this
entry's latest reading, not the date you are reading this.
“Grigòr, the Creator” (@grigor), 15,657 subscribers as measured 11 November 2026. Telegram Register, tgregister.com/channel/grigor.
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.