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 9 September 2026 and assigned it the closest of 31 fixed categories, at 83% 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.
Growth
32 measurements spanning 39 days, net -4,005. 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 58,829–64,036 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 32
Measured (UTC)
Subscribers
Change
16 Sept 2026, 02:57
59,430
-133
14 Sept 2026, 09:21
59,563
-158
12 Sept 2026, 18:42
59,721
-138
10 Sept 2026, 20:37
59,859
-309
7 Sept 2026, 16:16
60,168
-290
4 Sept 2026, 18:01
60,458
-127
3 Sept 2026, 02:36
60,585
-114
1 Sept 2026, 20:59
60,699
-96
31 Aug 2026, 17:35
60,795
-91
30 Aug 2026, 18:25
60,886
-61
29 Aug 2026, 20:13
60,947
-75
28 Aug 2026, 23:34
61,022
-118
28 Aug 2026, 02:08
61,140
-91
27 Aug 2026, 00:24
61,231
-88
26 Aug 2026, 03:22
61,319
-104
25 Aug 2026, 03:24
61,423
-97
23 Aug 2026, 20:24
61,520
-191
22 Aug 2026, 04:35
61,711
-165
20 Aug 2026, 18:44
61,876
-139
19 Aug 2026, 17:14
62,015
first reading
Engagement
20 posts held, back to 3 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 81 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
7.17%
avg views ÷ 59,430 subscribers
Avg views / post
4,260
6 posts measured
Reaction rate
0.383%
reactions ÷ views · ER floor
Posts in window
6
of 20 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 14 September 2026
Posts held
20 (3 July 2026 – 14 September 2026)
Views total
25,570
Reactions total
98
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
16 Sept 2026, 00:34 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
1m 08s
Average length
10s
Measured directly from 7 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
312 reactions across 20 posts, in 13 distinct kinds. The most used accounts for 63.1% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
197
63.1%
🔥
77
24.7%
👍
11
3.53%
👎
6
1.92%
💘
4
1.28%
😍
4
1.28%
❤🔥
3
0.962%
😁
3
0.962%
💋
2
0.641%
🤡
2
0.641%
🆒
1
0.321%
👏
1
0.321%
💩
1
0.321%
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 20 of the 20 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 312 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 3 July 2026 to 14 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.
ОСЕННЯЯ ПОРА - ПОВТОРЯЕМ НОВЫЙ ТРЕНД 🍂
Пошаговая инструкция как повторить в LavandaGPT:
⏺️ Переходим на LavandaGPT → Раздел Генерация изображения → Nano Banana 2
⏺️ Загружаем свое фото в хорошем качестве и вставляем промпт
ПРОМПТ 👇🏻
Фотореалистичный кинематографичный вертикальный портрет 9:16, кадр по колено/по талии, камера на уровне глаз, осенняя городская улица с кирпичными зданиями, большими окнами и яркой ора…
СЛУЧАЙНЫЙ ТОЛЧОК - ПОВТОРЯЕМ НОВЫЙ ТРЕНД 🔥
Пошаговая инструкция как повторить в LavandaGPT:
⏺️ Переходим на LavandaGPT → Раздел видео → Seedance 2.5
⏺️ Загружаем 3 фото из гайда → Ставим разрешение 9:16 и выбираем длительность 12 секунд
⏺️Берём промпт отсюда и вставляем: ВЗЯТЬ ПРОМПТ
Удиви своих друзей таким невероятным трендом 😉
ОТКРЫТКА НА ДЕНЬ ЗНАНИЙ 📚🍂
Пошаговая инструкция как повторить в Мелмане:
⏺️ Переходим в @Melman_MD_bot → Меню → Изображения
⏺️ Выбираем модель Nano Banana Pro → Выбираем формат
⏺️ Загружаем фото ребенка (в хорошем качестве, где отлично видны черты лица).
⏺️Вставляем промпт 👇
Создай поздравительную открытку ко Дню знаний. Изобрази ребенка с референсного фото, сходство 100%, в аккуратной школьной форме и с большим бук…
ЗАГАДОЧНАЯ ФОТОСЕССИЯ - НОВЫЙ ТРЕНД
Пошаговая инструкция как повторить в Мелмане:
⏺️ Переходим в @Melman_MD_bot → Меню → Изображения
⏺️ Выбираем модель Nano Banana Pro → Выбираем формат
⏺️ Загружаем свое фото (в хорошем качестве, где отлично видны черты лица).
⏺️Вставляем промпт 👇
Максимально фотореалистичная фотография, снятая на iPhone, вертикальный формат 3:4, RAW, 8K. Мрачный атмосферный дорогой lifestyle-моме…
ПРИРУЧАЕМ ДИКОГО ЛЬВА - ПОВТОРЯЕМ НАШУМЕВШИЙ ТРЕНД 🦁
Пошаговая инструкция как повторить в Neurosphere:
⏺️ Переходим на Neurosphere → Раздел видео → Seedance 2.5
⏺️ Загружаем свое фото в хорошем качестве → Ставим разрешение 9:16 и выбираем длительность 11 секунд
⏺️Берём промпт отсюда и вставляем: ВЗЯТЬ ПРОМПТ
Отправь другу который всегда хотел такого домашнего питомца 😆
ПРЫЖОК К САМОЛЕТУ - ПОВТОРЯЕМ НОВЫЙ ТРЕНД 🛩
Пошаговая инструкция как повторить в MashaGPT:
⏺️ Переходим на MashaGPT → Раздел видео → Seedance 2.0
⏺️ Загружаем свое фото в хорошем качестве → Ставим разрешение 9:16 и выбираем длительность 10 секунд
⏺️Вставляем промпт👇
Create a 10-second vertical 9:16 photorealistic cinematic video.
Use the uploaded face reference as the identity source for the main subject. Preserv…
СЕЛФИ С БУКЕТОМ МЕЧТЫ - НОВЫЙ ТРЕНД 💐
Пошаговая инструкция как повторить в Мелмане:
⏺️ Переходим в @Melman_MD_bot → Меню → Изображения
⏺️ Выбираем модель Nano Banana Pro → Выбираем формат
⏺️ Загружаем свое фото (в хорошем качестве, где отлично видны черты лица).
⏺️Вставляем промпт 👇
Сохранить внешность на 100%. Не изменять черты лица, пропорции. Зеркальное селфи, спонтанный ночной кадр на кровати с огромным букетом …
ПОВЕЛИТЕЛЬ ДРАКОНОВ - ПОВТОРЯЕМ ТРЕНД 🐲
Пошаговая инструкция как повторить в Study:
⏺️ Переходим на StudyAi → Все нейросети → Seedance 2.0
⏺️ Загружаем свое фото в хорошем качестве → Ставим разрешение и выбираем любую длительность
⏺️Вставляем промпт👇
CHARACTER : [IMAGE REFERENCE] wearing a dark hooded jacket with the hood down, natural tousled hair, calm expression
LOCATION
A grassy hilltop clearing surrounded b…
📸 Новый Свадебный Образ в пару кликов!
Переходим в @LakiNeuro_bot → 📸Фотосессия → Готовые образы → Праздники → Свадьба → Невеста в оранжерее → Выбрать → Сгенерировать
Через несколько кликов получаем изумительную фотосессию в белом платье 🩰
- Если у вас ещё нет аватара, отправьте команду /start в боте и создайте его бесплатно по инструкции.
- Если нужна помощь или хотите посмотреть примеры фотосессий других людей…
ЧЕЛОВЕК ПАУК ВОЗВРАЩАЕТСЯ - НОВЫЙ ТРЕНД 👽
Пошаговая инструкция как повторить в Мелмане:
⏺️ Переходим в @Melman_MD_bot → Меню → Изображения
⏺️ Выбираем модель Nano Banana Pro → Выбираем формат
⏺️ Загружаем свое фото (в хорошем качестве, где отлично видны черты лица).
⏺️Вставляем один промптов 👇
На крыше :
Используй загруженное фото как референс лица. Преврати человека в героя в стиле Человека-паука, сидящего на краю…
📸 Новый Летний Образ в пару кликов!
Переходим в @LakiNeuro_bot → 📸Фотосессия → Готовые образы → Тренды → Земляника и летняя дача → Собирает клубнику → Выбрать → Сгенерировать
Через несколько кликов получаем атмосферную фотосессию прямо как на даче 🏡🍓
- Если у вас ещё нет аватара, отправьте команду /start в боте и создайте его бесплатно по инструкции.
- Если нужна помощь или хотите посмотреть примеры фотосессий д…
ЛЕВ НА ДЕНЬ РОЖДЕНИЯ - НОВЫЙ ТРЕНД 🦁
Пошаговая инструкция как повторить в Study:
⏺️ Переходим на StudyAi → Все нейросети → Seedance 2.0
⏺️ Загружаем свое фото в хорошем качестве → Ставим 9:16 и 6 сек
⏺️Вставляем промпт👇
A 6-second cinematic birthday video. Use the attached reference image for the person's face and preserve their exact identity, facial features, age and skin tone throughout, no morphing or distorti…
❤20
Showing the 12 most recent of 20 posts we hold for @LakiNeuro. 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.
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.
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 16 September 2026 — this
entry's latest reading, not the date you are reading this.
“Лаки нейро” (@LakiNeuro), 59,430 subscribers as measured 16 September 2026. Telegram Register, tgregister.com/channel/LakiNeuro.
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.