Art & design — 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 65% 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
31 measurements spanning 42 days, net -26. 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 18,787–18,832 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 31
Measured (UTC)
Subscribers
Change
17 Sept 2026, 15:17
18,792
-3
15 Sept 2026, 10:18
18,795
-4
13 Sept 2026, 18:42
18,799
-4
12 Sept 2026, 03:38
18,803
+3
9 Sept 2026, 20:00
18,800
-11
6 Sept 2026, 11:58
18,811
-5
4 Sept 2026, 00:42
18,816
+1
1 Sept 2026, 15:37
18,815
-6
31 Aug 2026, 12:38
18,821
+6
30 Aug 2026, 11:05
18,815
+7
29 Aug 2026, 08:13
18,808
-9
28 Aug 2026, 06:37
18,817
+3
27 Aug 2026, 06:17
18,814
+1
26 Aug 2026, 05:25
18,813
+6
25 Aug 2026, 07:42
18,807
+2
24 Aug 2026, 10:28
18,805
-5
22 Aug 2026, 18:59
18,810
+2
21 Aug 2026, 11:19
18,808
+2
20 Aug 2026, 13:54
18,806
+6
19 Aug 2026, 13:13
18,800
first reading
Engagement
63 posts held, back to 4 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 56 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
4.94%
avg views ÷ 18,792 subscribers
Avg views / post
928
19 posts measured
Reaction rate
3.00%
reactions ÷ views · ER floor
Posts in window
20
of 63 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 2 September 2026
Posts held
63 (4 August 2026 – 2 September 2026)
Views total
17,632
Reactions total
529
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Sept 2026, 02:11 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
5m 44s
Average length
57s
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
1,526 reactions across 57 posts, in 8 distinct kinds. The most used accounts for 72.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,105
72.4%
👍
115
7.54%
❤🔥
114
7.47%
🔥
76
4.98%
🎉
59
3.87%
😁
40
2.62%
👏
10
0.655%
🤩
7
0.459%
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 61 of the 63 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 1,635 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 63 most recent posts we hold, published 4 August 2026 to 2 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.
Графика Левитана — это точная и сдержанная работа с линией, силуэтом и тоном ✏️
Даже лаконичные зарисовки передают характер пейзажа и его настроение.
🌿 На курсе «Пленэры. Линер и ручка» Полина Абдулаева показывает, как наблюдать за натурой, находить в ней главное и переводить свои впечатления в выразительную графику.
7 простых сюжетов, которые можно превратить в стикер ⭐
Стикеры могут быть не только милыми картинками, но и отличной практикой для художника ✍️
В этой карусели собрали 7 сюжетов, которые можно превратить в стикеры: каждый из них помогает потренировать отдельные художественные навыки — от передачи фактур и бликов до работы с цветом, формой, композицией и деталями.
❓ А какие предметы вы бы превратили в стикеры?
👉 Ку…
Как фабрика превратилась в музей 🍬
В Музее русского импрессионизма проходит выставка «Хрупкие причуды: от кондитерской к музею», посвящённая истории места, в котором сегодня находится музей.
🥮 Когда-то здесь работала фабрика «Большевик», выпускавшая кондитерские, а в какое-то время — парфюмерные изделия. Экспозиция обращается к этой истории через произведения искусства, архивные материалы, предметы, фотографии и со…
Армен Карапетьянц про особенности работы маслом 🤏
✅Как выбрать кисти для масла
✅Эффект свечения маслом
✅Как подготовить холст к живописи
✅Лайфхак для пластичности краски
🤏 Наши курсы по масляной живописи
С вами снова #день_художественных_работ
Раз в неделю мы публикуем пост, в комментариях к которому вы можете делиться своим творчеством:
работами по урокам школы Художник Онлайн, а также самостоятельными работами 🙌
Все остальные фотографии, не относящиеся к теме постов или конкурсов, будут удаляться.
❗️Работы принимаются до 22.00 (мск) сегодняшнего дня (29 августа).
Также мы просим вас соблюдать следующие обновленн…
Графика Василия Поленова - хороший пример того, как наблюдение превращается в образ ✍️
Художник не стремится рассказать обо всём сразу в каждой работе: иногда он выбирает несколько точных линий, намечает свет и пространство, и оставляет зрителю возможность дорисовать остальное.
На курсе «Пленэры. Линер и ручка» вы тоже будете учиться видеть в натуре главное и переводить свои наблюдения в выразительную графику ☘️
👉 …
Дни открытых дверей подошли к концу: ГАЛЕРЕЯ ВАШИХ РАБОТ 🎉
Сегодня мы предлагаем вам обменяться работами, которые вы успели выполнить за время акции и поделиться впечатлениями в комментариях.
Что нового вы открыли для себя? Какой сюжет был самым интересным? Ждём ваших отзывов ⤵️
🗓️ Мы календарь перевернем и встретимся 3 сентября в 19:30(мск) на мастер-классе Полины Абдулаевой: будем писать портрет Михаила Шуфутинского с его узнаваемой улыбкой, очками с цветными линзами, бородой и ярким сценическим образом.
✍️ На занятии мы разберем работу с портретом по фотографии, научимся передавать объём гуашью и создадим живописный портрет, где важны сходство, характер и детали внешности героя.
✅Регист…
😁40👏7🤩6❤4❤🔥1
Showing the 12 most recent of 63 posts we hold for @hudozhnik_online. 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.
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.
Собака-рисовака @sobaka_risovaka · 32,926 Telegram ranks this channel #3 of 90 here — alongside 89 others — read 4 September 2026
АНТИПИН.АРТ @antipinart · 31,926 Telegram ranks this channel #8 of 88 here — alongside 87 others — read 5 September 2026
KalachevaSchool @kalachevaSchool · 21,993 Telegram ranks this channel #11 of 92 here — alongside 91 others — read 22 September 2026
Я художник | Рисуем всей семьей @i_am_artis · 106,028 Telegram ranks this channel #48 of 77 here — alongside 76 others — read 15 August 2026
Художник, рисуй! | Digital Art образование @simpleartist · 59,075 Telegram ranks this channel #50 of 89 here — alongside 88 others — read 22 August 2026
Красный Карандаш @krasniy_karandash · 28,248 Telegram ranks this channel #73 of 86 here — alongside 85 others — read 9 September 2026
This channel appears in 6 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 17 September 2026 — this
entry's latest reading, not the date you are reading this.
“Художник Онлайн” (@hudozhnik_online), 18,792 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/hudozhnik_online.
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.