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Channel

LLM под капотом

@llm_under_hood

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Handles named that no longer answer · Telegram's recommendations · Cite this entry

28,682subscribers

+153 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001943579488
TypeChannel
Username@llm_under_hood
DescriptionКанал про разработку продуктов на базе LLM/ChatGPT. Выжимка важных новостей и разборы кейсов. Чтобы писать - напишите боту @llm_under_hood_bot Рекламы в канале - нет. За комменты от ботов баним вместе с хозяином.
CreatedBetween 1 April 2023 and 31 October 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live15 August 2026
Measurements held10
Confirmed unchanged1 time, most recently 15 August 2026
On Telegramt.me/llm_under_hood

Growth

28,52928,68228,605.56 August 2026 — 28,529 subscribers7 August 2026 — 28,570 subscribers8 August 2026 — 28,576 subscribers9 August 2026 — 28,584 subscribers10 August 2026 — 28,596 subscribers11 August 2026 — 28,599 subscribers12 August 2026 — 28,616 subscribers13 August 2026 — 28,628 subscribers14 August 2026 — 28,654 subscribers15 August 2026 — 28,682 subscribers6 August 202615 August 2026
10 measurements spanning 10 days, net +153. 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 28,506–28,705 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
15 Aug 2026, 20:0428,682+28
14 Aug 2026, 10:2528,654+26
13 Aug 2026, 02:5828,628+12
12 Aug 2026, 04:3128,616+17
11 Aug 2026, 04:0528,599+3
10 Aug 2026, 04:5728,596+12
9 Aug 2026, 03:1128,584+8
8 Aug 2026, 04:1428,576+6
7 Aug 2026, 04:2328,570+41
6 Aug 2026, 06:0228,529first reading

Engagement

21 posts held, back to 2 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 23 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
49.4%
avg views ÷ 28,682 subscribers
Avg views / post
14,200
12 posts measured
Reaction rate
0.67%
reactions ÷ views · ER floor
Posts in window
12
of 21 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
WindowRolling 30 days · latest post in window 14 August 2026
Posts held21 (2 July 202614 August 2026)
Views total170,050
Reactions total1,139
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken16 Aug 2026, 04:49 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
373
Videos
17
Links
684

Lifetime counters from Telegram’s own channel header, read 16 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Video runtime
3m 21s
Average length
3m 21s

Measured directly from 1 video 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

1,919 reactions across 21 posts, in 17 distinct kinds. The most used accounts for 30.5% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥58630.5%
54828.6%
👍49725.9%
😢583.02%
🤗452.34%
😁432.24%
👏402.08%
🤣201.04%
🤯190.99%
🤔160.834%
😱120.625%
🥰120.625%
🙏70.365%
💯60.313%
🤝50.261%
🎄30.156%
20.104%

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 21 of the 21 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 1,919reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 21 most recent posts we hold, published 2 July 2026 to 14 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.

Recent posts

14 Aug 2026, 03:36 UTC≈5,690 views58 reactionsread 16 August 2026

Posted without readable text

🔥27👍1412🤗3👏1💯1

10 Aug 2026, 08:21 UTC≈9,530 views55 reactionsread 16 August 2026

Ответ на предыдущий вопрос. На реализацию фичи у кодекса ушло 12 минут и меньше процента подписки (как было 89, так 89 и осталось). Я не за компом, поэтому пришлось попросить Codex сделать и прислать скриншоты. Вложу их в комментарии. В коде много оверинжиниринга не заметил, только не понравилось, как сделана работа с выкачкой архивов. Но я все равно сейчас откачу назад все изменения! Фишка в том, что в этом про

👍27👏105😱5🤗4🤣4

10 Aug 2026, 07:12 UTC≈8,300 views76 reactionsread 16 August 2026

Posted without readable text

🔥4215🤗10🤣5👍3💯1

9 Aug 2026, 05:28 UTC≈9,130 views62 reactionsread 16 August 2026
Photo

Приятный лайфхак - просить Codex писать красивые новости про прогресс своих проектов Ему это ничего не стоит (ибо в ~/.codex/sessions есть все логи всех проектов), а вот со стороны посмотреть на прогресс во время отпуска - приятно. К слову, Agentic OS на скриншоте - это не очередная AI Native среда для построения следующего единорога (такие продукты сейчас пытаются писать почти все), а просто наглядный пример моего

33👍14🔥5🤝3🥰3🤗2💯1😁1

6 Aug 2026, 08:28 UTC≈11,400 views71 reactionsread 16 August 2026
Photo

В этом месяце мы путешествуем. Поэтому время наедине с лаптопом ограничено. Поэтому я и завел codex демонов на linux сервере. Самое главное, наконец, доделал новую версию full-stack event-driven BDD фреймворка, про который обсуждали на вебинарах по AI Coding. Про подход к BDD спекам в продуктах (еще в эру до LLM) я рассказывал в этой истории. Сейчас получилось сделать их full-stack, привязать к UI компонентам (напри

36👏20🔥12🤗2🤔1

3 Aug 2026, 09:26 UTC≈14,000 views127 reactionsread 16 August 2026
Photo

Я наконец, запустил свой Codex на Linux сервере, с прямым контролем из-под мобильного ChatGPT приложения (через `remote-control`). Это дает возможность запускать разные задачи нативно без привязки к маку. NB: До этого пробовал разные харнесы со своими telegram интеграциями, но все это не то. Хотелось именно нативного. Для этого: # ставим `codex` CLI одной из последних верси npm install -g @openai/codex@latest #

👍7921🔥17🤔3🤗3😁3🎄1

1 Aug 2026, 16:34 UTC≈13,400 views92 reactionsread 16 August 2026
Photo

Бенчмарк Deepseek V4 Flash 0731 - попадание на Парето-фронтир по стоимости Новая версия Deepseek V4 стала получше своего предшественника. Возможно, там что-то подкрутили с reasoning, т.к. бенчмарк новой версии работал в 2.5 раза дольше и потратил больше денег. Но это стоило того, т.к. по соотношению цена/качество в долгоиграющих агентских задачах эта модель попала на Pareto-фронтир рядом с gpt-oss-120b Deepseek V4

41🔥30👍19🤗2

25 Jul 2026, 03:36 UTC≈16,900 views95 reactionsread 16 August 2026
Photo

LLM Benchmark Opus 5 на агентских задачах в бизнесе Я померил два варианта Anthropic Opus 5 - обычный и Fast. Последний работает раза в два быстрее, но стоит раза в два дороже. Уровень ответов при этом идентичный. Очень высокий уровень AI Code (tool generation/use) и всего по два "прокола" безопасности. В итоге модели заняли 4 и 5 места по точности, если смотреть без учета скорости и цены. А если же быть реалистичн

👍6126🎄2🔥2🤔2🤗2

23 Jul 2026, 04:25 UTC≈14,500 views56 reactionsread 16 August 2026
Photo

Новые LLM на фронтире бенчмарка - просто добавь Cerebras Помните, совсем недавно Gemma 4 31B пододвинула фронтир скорости на нашем бенчмарке LLM после запуска на Cerebras? Я попробовал запустить gpt-oss-120B на нем же, перебирая разные варианты reasoning. И выяснилось, что все три версии - high reasoning, medium и low попадают на speed frontier, двигая его вперед. А medium reasoning при этом еще и оказывается на co

👍26🔥1662🤗2🤯2🤔1😢1

22 Jul 2026, 08:48 UTC≈12,800 views172 reactionsread 16 August 2026

Posted without readable text

86🔥59👍17🤗6🤯2🤔1😢1

21 Jul 2026, 15:23 UTC≈11,000 views70 reactionsread 16 August 2026
Photo

Новая модель на фронтире - Gemma 4 31B (Cerebras) @AigizK сегодня попробовал Gemma 4 31B на Cerebras и сильно хвалил результаты. Поэтому попробовал запустить на агентском бенчмарке под бизнес-задачами и я. Cerebras - это такой производитель гигантских чипов для запуска моделей. Их wafer-scale engines раз в 50 больше самых крупных GPU. Железо получается очень дорогое и специализированное, зато позволяет запускать не

🔥4118🤗9🤯1😢1

20 Jul 2026, 15:48 UTC≈43,400 views205 reactionsread 16 August 2026
Photo

Kimi K3 - в топе бенчмарка LLM для агентов По очкам модель сравнима с GPT-5.5 Pro, но раз в 15 дешевле и раза в 2 быстрее. С такими показателями она автоматом попадает на оба Парето-Фронта, сдвигая их. Эта модель с открытыми весами размером аж в 2.8T параметров, веса обещают выложить в открытый доступ 27 июля. Из минусов - гигантский размер и большее количество пропущенных уязвимостей. Но плюсы перевешивают. Модел

95👍58🔥36🤔8🤯4🤣2🙏2

Showing the 12 most recent of 21 posts we hold for @llm_under_hood. 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.

Citation-graph rank

Citation-graph rank — 3,743 of 1,481,217entries 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.

Forward network

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 46 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.

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.

эйай ньюз
@ai_newz · 96,023
Telegram ranks this channel #5 of 94 here — alongside 93 others — read 16 August 2026
Machinelearning
@ai_machinelearning_big_data · 285,509
Telegram ranks this channel #8 of 95 here — alongside 94 others — read 10 August 2026
Denis Sexy IT 🤖
@denissexy · 134,889
Telegram ranks this channel #12 of 95 here — alongside 94 others — read 13 August 2026

This channel appears in 3 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 15 August 2026 — this entry's latest reading, not the date you are reading this.

“LLM под капотом” (@llm_under_hood), 28,682 subscribers as measured 15 August 2026. Telegram Register, tgregister.com/channel/llm_under_hood.

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.