Local community — 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 4 October 2026 and assigned it the closest of 31 fixed categories, at 45% 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
8 measurements spanning 59 days, net +23. 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 241–270 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
28 Oct 2026, 07:01
267
+8
21 Oct 2026, 16:49
259
+2
13 Oct 2026, 12:57
257
+2
4 Oct 2026, 06:15
255
-2
10 Sept 2026, 01:16
257
+9
31 Aug 2026, 03:55
248
+4
30 Aug 2026, 10:45
244
no change
30 Aug 2026, 10:30
244
first reading
Engagement
6 posts held, back to 18 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 1 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 6 posts for this entry, the most recent from 29 August 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
22s
Average length
11s
Measured directly from 2 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
127 reactions across 6 posts, in 7 distinct kinds. The most used accounts for 31.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
40
31.5%
custom 5400189830120355437
30
23.6%
❤🔥
29
22.8%
custom 5467379976376437805
15
11.8%
custom 5467626468844523380
7
5.51%
💘
4
3.15%
🔥
2
1.57%
Custom emoji. 3 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 are Telegram’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 6 of the 6 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 127 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 6 most recent posts we hold, published 18 August 2026 to 29 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.
Вот так прошла наша книжная встреча 📚☕️
Спасибо каждому, кто был с нами! За ваши мысли, разговоры и ту самую тёплую атмосферу 🤎
А мы уже ждём новой встречи:
🍂 6 сентября в 18:00
«Классика между строк: о чём молчат все великие романы»
Проведём уютный осенний вечер за чашкой кофе, поговорим о книгах и смыслах, которые часто остаются между строк.
До встречи! 🤎
📚 Завтра в HASH пройдёт книжная встреча — и для её участников будет действовать специальный промокод.
Назовите при заказе промокод «КНИГА» и получите скидку на все напитки ☕️
Промокод действует только для участников книжной встречи и только в день мероприятия.
Увидимся завтра в 15:00 🤍
Как читать классику и получать удовольствие? 📚
Вы уверены, что классика — это скучно и тяжело? Давайте развеем этот миф.
Поговорим о том, как перестать воспринимать чтение как школьную повинность и превратить его в живой интерес. Как читать в метро или перед сном и не терять нить. И почему романы, написанные сто лет назад, порой оказываются острее современных бестселлеров.
Без заумных терминов — только живой разго…
Осень в HASH начинается со встреч 💙
Собрали события на конец августа и сентябрь: книжные встречи, Новатория, моктейльная неделя и ещё кое-что, о чём пока не будем рассказывать 👀
Вбирайте, куда хотите прийти, и сохраняйте даты
Увидимся в HASH💙
Клубника, томат и красное безалкогольное вино — мэтч, которого не ожидаешь 🍓
Яркий, сочный, с приятной ягодной кислинкой и лёгкой винной терпкостью. А содовая добавляет свежести и собирает всё воедино🍷
Не пытайтесь представить вкус. Просто попробуйте😋
Showing the 6 most recent of 6 posts we hold for @hash_coffee_ru. 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
Named by 1 registered channel — 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.
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 28 October 2026 — this
entry's latest reading, not the date you are reading this.
“Hash Coffee” (@hash_coffee_ru), 267 subscribers as measured 28 October 2026. Telegram Register, tgregister.com/channel/hash_coffee_ru.
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.
