Ну да, было.
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Channel
@sonya_aesthetics
On this record: Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Cite this entry
3,162subscribers
-1 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1001701120514 |
|---|---|
| Type | Channel |
| Username | @sonya_aesthetics |
| Created | 11 January 2022 — measured — cross-checked against a third-party dataset (ext.tg_channel) |
| First recorded | 7 August 2026 |
| Last confirmed live | 17 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 17 August 2026 |
| On Telegram | t.me/sonya_aesthetics |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 17 Aug 2026, 15:55 | 3,162 | -1 |
| 7 Aug 2026, 14:28 | 3,163 | no change |
| 7 Aug 2026, 07:45 | 3,163 | first reading |
18 posts held, back to 11 September 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 3 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 4 August 2026 |
|---|---|
| Posts held | 18 (11 September 2025 – 4 August 2026) |
| Views total | 3,978 |
| Reactions total | 82 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 7 Aug 2026, 23:45 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.
Measured directly from 3 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.
487 reactions across 18 posts, in 8 distinct kinds. The most used accounts for 28.7% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🔥 | 140 | 28.7% | |
| custom 5438606753509957469 | 108 | 22.2% | |
| custom 5348443467137690824 | 101 | 20.7% | |
| ❤ | 63 | 12.9% | |
| custom 5442741651669795615 | 42 | 8.62% | |
| custom 5390883980314682758 | 26 | 5.34% | |
| ❤🔥 | 6 | 1.23% | |
| 💯 | 1 | 0.205% |
Custom emoji. 4 of the rows above are Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them areTelegram’s.
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 18 of the 18 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 487reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 18 most recent posts we hold, published 11 September 2025 to 4 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.
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @sonya_aesthetics. 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 18 most recent posts we hold for this entry, published 11 September 2025 to 4 August 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.
Ну да, было.
custom 543860675350995746925
Потестила я вашу новую видеомодель MiniMax H3. 🎩 Конечно же, первым делом я отправила её сдавать экзамен по моему любимому фигурному катанию. Это вообще отличный стресс-тест для видеомоделей: тут нужно одновременно понимать анатомию, перенос веса, вращения, положение рук и ног + не превращать человека в "пластилинового" между соседними кадрами. На первый взгляд результат выглядит не так уж плохо для модели с открыты…
❤🔥5custom 54427416516697956154❤3💯1
Posted without readable text
🔥16custom 54386067535099574697❤🔥1
Ага, а керри Team Yandex должен спроектировать масштабируемую систему фарма крипов, но после найма его отправят ставить варды. 😎 https://t.me/ebaresearch/3842
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Теперь это мой любимый мем https://t.me/toshoseti/1898
🔥21custom 543860675350995746910custom 54427416516697956152
Что слушает твой коллега, который не разобрался в настройках модели, выкрутил всё на максимум и потратил весь месячный лимит по токенам за пару часов
custom 543860675350995746927🔥10custom 54427416516697956153
В древние времена, когда люди писали ещё код своими ручками (и думали головой) и использовали для этого всякие редакторы кода Atom или SublimeText, а потом уже и VS Code, я очень любила устанавливать всякие плагины по типу плагина с Nyan Cat или плагин с счётчиком комбо, который увеличивался, были ещё всякие фейерверки и искры, когда ты начинал быстро и без ошибок печатать код. Сейчас я люблю находить подобные штуки…
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Упс ☹️ Надеюсь, что и когда его ласково называют, он тоже это записывает.. https://t.me/data_secrets/8959
custom 544274165166979561510custom 54386067535099574696
Люблю периодически у Claude Code запрашивать фидбек о наших сессиях через команду /insights. Кстати, это очень крутая фича, которая позволяет качественно улучшить процесс вайб-кодинга. Жду, пока там появится пункт о том, чтобы я его меньше оскорбляла и материла. Стоп мне неприятно 😨
🔥22custom 54386067535099574693custom 54427416516697956151
Советую почитать. Очень занятно отметить, что некоторые люди до сих пор не научились самостоятельно информацию в интернете искать и анализировать, а тут нейросетевая модель хакнула бенчмарк для её же оценки. 🥵 https://t.me/dealerAI/1724
custom 54386067535099574695🔥3custom 54427416516697956151
Пока админ перебиралась по работе на Балканы, тут челики из лабы Сингапурского университета представили Kiwi-Edit — опенсорс фреймворк для редактирования видео, который объединяет и текстовые инструкции, и визуальные референсы. Что прикольного: ☝️ можно редактировать видео просто текстом (например, «замени куртку на синий пуховик») или загрузить картинку-референс, чтобы модель сама скопировала стиль или объект отту…
custom 544274165166979561512🔥8custom 54386067535099574693
Давно я не писала в свой канал и пора бы возобновить его жизнь. 🙂 Отчасти это из-за того, что телеграм-каналов стало так много, особенно которые рассказывают про нейронные сети, что я немного потерялась в смысле ведения своего канала. Писать просто разбор пейперов будто уже не совсем актуально, когда тебе его может разобрать какой-нибудь NotebookLM. Понятно, что он не даст какую-то экспертную оценку с точки зрения оп…
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Showing the 12 most recent of 18 posts we hold for @sonya_aesthetics. 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.
Citation-graph rank — 902,931 of 1,480,975entries 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republishes
Channels on the register whose posts this channel has forwarded.
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.
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 17 August 2026 — this entry's latest reading, not the date you are reading this.
“Соне нравится (или нет)” (@sonya_aesthetics), 3,162 subscribers as measured 17 August 2026. Telegram Register, tgregister.com/channel/sonya_aesthetics.
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.