🔥 Собрали нейросети для жизни, работы и учебы в одном месте
👉🏽 TG BOT для генераций —
https://t.me/study24ai_bot?start=ref=source-telegram_medium-tgbot
• Seedance 2.0, Nano Banana PRO, Kling, ChatGPT и др
N° 6887192669
Created
Between 1 March 2018 and 31 August 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
Technology — 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 8 August 2026 and assigned it the closest of 31 fixed categories, at 99% 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
33 measurements spanning 50 days, net +26,259. 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 343,734–377,871 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 33
Measured (UTC)
Subscribers
Change
26 Sept 2026, 07:17
373,932
+12,061
17 Sept 2026, 11:57
361,871
+1,585
15 Sept 2026, 11:17
360,286
+949
13 Sept 2026, 19:38
359,337
+1,583
11 Sept 2026, 22:21
357,754
+1,629
9 Sept 2026, 09:59
356,125
+1,768
5 Sept 2026, 23:59
354,357
+747
3 Sept 2026, 20:20
353,610
+400
2 Sept 2026, 14:08
353,210
+68
1 Sept 2026, 15:38
353,142
+53
31 Aug 2026, 18:08
353,089
-245
30 Aug 2026, 17:25
353,334
+44
29 Aug 2026, 17:04
353,290
+162
28 Aug 2026, 14:33
353,128
-155
27 Aug 2026, 14:55
353,283
+308
26 Aug 2026, 16:24
352,975
+278
25 Aug 2026, 15:23
352,697
+278
24 Aug 2026, 13:29
352,419
+453
22 Aug 2026, 17:36
351,966
+599
21 Aug 2026, 08:54
351,367
first reading
Engagement
116 posts held, back to 3 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 111 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
2.98%
avg views ÷ 373,932 subscribers
Avg views / post
11,100
70 posts measured
Reaction rate
0.284%
reactions ÷ views · ER floor
Posts in window
70
of 116 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 29 September 2026
Posts held
116 (3 August 2026 – 29 September 2026)
Views total
780,300
Reactions total
2,219
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
29 Sept 2026, 20:06 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
Photos
≈1,100
Videos
≈381
Links
≈803
Lifetime counters from Telegram’s own channel header, read 29 September 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Video runtime
17m 55s
Average length
30s
Measured directly from 36 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
3,729 reactions across 116 posts, in 39 distinct kinds. The most used accounts for 40.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,509
40.5%
🔥
1,198
32.1%
👍
474
12.7%
👏
141
3.78%
⚡
77
2.06%
😁
61
1.64%
❤🔥
43
1.15%
🍓
28
0.751%
🤡
23
0.617%
🐳
14
0.375%
👎
14
0.375%
🤯
14
0.375%
😍
13
0.349%
😭
11
0.295%
🙏
11
0.295%
🫡
11
0.295%
💋
10
0.268%
😱
8
0.215%
🤣
8
0.215%
🆒
7
0.188%
19 further kinds
54
1.45%
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 116 of the 116 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 3,729 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 116 most recent posts we hold, published 3 August 2026 to 29 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.
Telegram Stars
Stars received
15
across the posts below
Posts paid on
14
of 116 we hold a reading for · 12%
Most on one post
2
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @study24ai. 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 116 most recent posts we hold for this entry, published 3 August 2026 to 29 September 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.
Два тренда, которые прямо сейчас набирают миллионы просмотров 🔥
Скорее всего, вы уже видели их в ленте, и, возможно, не один раз
Мы сделали двух агентов, чтобы вы могли повторить эти ролики сами. Промпты писать не нужно
🤩 Повторить очень просто: выбираете тренд, загружаете фото персонажей
СОЗДАТЬ ВИДЕО
Ставьте реакцию, если хотите больше трендовых видео
🤩 StudyAI САЙТ
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Что нового:
🤩 Отвечает более чем на 30% быстрее Sonnet 5
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🤩 В рабочих задачах вроде отчётов, анализа и деловых текстов результат почти как у Opus 5.5
🤩 Пишет понятнее: ответы стали чётче и лучше структурированы
Отлично подходит для повседневных задач: нап…
9 ИИ-агентов, которые берут рутину на себя
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Часть этой работы можно отдать ИИ-агентам на StudyAI
Не нужно писать никакие промпты, вы просто загружаете материалы, описываете, что нужно, и получаете готовый результат
Попробовать ИИ-агентов 🔥
Выберите одну задачу, которая отни…
Приглашайте друзей, получайте токены 🎁
У нас запущена реферальная программа. В рамках нее вы можете получать 20% от токенов первой оплаты друга
По такой системе можно получить до 2510 токенов за первую покупку друга
Как участвовать:
🤩 В личном кабинете вас уже ждёт персональная ссылка и промокод
🤩 Отправьте её другу
🤩 Друг оплачивает подписку
🤩 В течение 3 дней вам зачисляются токены в личный кабинет
Приглашайте…
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Бывает, что нейросеть отвечает не то, что нужно? Чаще всего дело не в модели
Нейросеть отвечает ровно на то, что написано в запросе, и если главное в промпт не попало, в ответе его тоже не будет
Мы собрали короткий курс во Вконтакте о том, как писать запросы, чтобы получать нужный результат:
🤩 7 уроков, по одному в день
🤩 5–7 минут на чтение
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Трендовое видео за два клика 🔥
Этот танец уже набирает сотни тысяч просмотров, и теперь вы можете повторить его сами
Мы сделали для него отдельного бота, поэтому промпты писать не нужно
Как сделать:
🤩 Открывайте бота — перейти
🤩 Загружайте фото людей, которые должны быть в видео
🤩 Получайте готовое видео
Вот и всё! Можно танцевать одному, с подругой, второй половинкой или всей семьёй
Присылайте свои видео в ком…
GPT 6 Sol и GPT 6 Luna на StudyAI
Что нового:
🤩 Sol ошибается примерно в 2 раза реже прошлой версии и по надёжности почти догоняет флагманскую GPT 6 Astra
🤩 Sol сильно прокачалась в коде: по тестам на программирование держится на уровне топовых моделей, а стоит заметно дешевле
🤩 Luna стала умнее и лучше справляется с многошаговыми задачами
🤩 Обе модели пишут понятнее: меньше заумных терминов и странных оборотов
Ка…
Напоминаем: конкурс на лучшую идею ИИ-агента ещё идёт
Предложите идею и заберите 10 000 токенов
В StudyAI уже работают ИИ-агенты для создания карточек товаров, генерации документов, презентаций, расшифровки встреч, генератора сайтов, кода, фотосессий и замены лица
Все они закрывают конкретную задачу целиком, без промптов и дополнительных настроек нейросети
Мы хотим знать, какого агента вам не хватает 🔥
🤩 Автор л…
Claude Opus 5.5 на StudyAI
Что нового:
🤩 По качеству работы приближается к топовой Fable 5.1, при этом доступнее по цене
🤩 Генерирует ответ более чем на 30% быстрее предыдущей версии
🤩 Хорошо находит и исправляет ошибки в коде, доводит длинные многошаговые задачи до конца
🤩 Стала общаться естественнее: точнее расставляет приоритеты в ответе и лучше следует вашим инструкциям по стилю
Это новая топовая модель от Ant…
Grok 4.7: модель, которая не бросает сложную задачу на середине
xAI выпустили новую модель, и она уже доступна в StudyAI. Grok 4.7 заменяет предыдущее поколение Grok 4.6
Протестировать Grok 4.7
Что изменилось:
🤩 Дольше и внимательнее работает над сложными задачами
🤩 Сама проверяет свой ответ перед тем, как показать его вам
🤩 Держит в памяти контекст объёмом до 500 тысяч токенов, подходит для больших документов и …
В «Реальных пацанах» теперь может сняться кто угодно, даже кот 🐱
Seedance 2.5 может заменить главного героя на любого другого персонажа. При этом сохранит исходную обстановку, движения и звук
Получается узнаваемая сцена, только в главной роли теперь не Коля, а тот, кого выберете вы
Трендовый формат подходит:
🤩 Для личного блога
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Раньше под коммерческие проекты переснимали сцены из известных …
Как сократить время на рутинные задачи
Если вы ведёте свой бизнес, наверняка знаете это чувство: собрать презентацию для клиента, оформить договор, разобрать запись созвона, запустить сайт под новый продукт. Одни и те же задачи каждый раз отнимают часы
Упростить рутину можно с помощью ИИ-агентов на StudyAI
🤩 Генерация презентаций
Опишите тему и что должно быть на слайдах, агент подберёт оформление по теме или соб…
🔥31❤8👍5👏2
Showing the 12 most recent of 116 posts we hold for @study24ai. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Posts edited after publishing
@study24ai edited 3 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
21 August 2026
Most recent edit
11 September 2026
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
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.
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.
Domains linked from posts
One domain this channel’s own posts have linked to, measured by scanning the post bodies themselves — not the channel’s description, which is the separate Declared links section below when this entry has one. Appearing here is not a claim about who runs the linked site or why the channel linked to it; an advertisement, a news citation and a malicious link all leave the same kind of row.
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 26 September 2026 — this
entry's latest reading, not the date you are reading this.
“StudyAI | Нейросети” (@study24ai), 373,932 subscribers as measured 26 September 2026. Telegram Register, tgregister.com/channel/study24ai.
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.