Твой личный мульти-ИИ помощник в Telegram.
Десятки моделей: ChatGPT, Claude, Gemini, Nano Banana, Kling, Deepseek, Suno, Veo и др — всё в одном месте.
Плати только за то, что создал. Без подписок и скрытых списаний.
👉🏻 @okigpt_bot
Created
Between 1 September 2025 and 31 December 2025 — 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-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 95% 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.
Observations
These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.
Views per post sit far below this size band
51.3 average views per post against 14,806 subscribers — an engagement rate of 0.346%. Across the 21,335 registered channels in the same cohort — 10,000–31,621 subscribers, posting mainly in Russian — the middle half sit between 5.84% and 23.6%, with a median of 12.1%.
What this was computed from
Window
30 days (6 October 2026 – 5 November 2026)
Posts measured
17 of 17 published in the window (17 exact, 0 rounded by Telegram)
Views totalled
872
Mature posts only
0.446% over 12 posts read at least 24h after publication
When this is recorded. A channel is listed here only when its engagement rate sits at or below the 1st percentile of its cohort and is at least 3× away from that cohort’s median — below it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal. A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the key err_low, last confirmed 5 November 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.
Growth
65 measurements spanning 97 days, net -4,835. 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 13,702–19,987 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 65
Measured (UTC)
Subscribers
Change
12 Nov 2026, 11:09
14,427
-128
10 Nov 2026, 11:11
14,555
-61
8 Nov 2026, 21:00
14,616
-114
7 Nov 2026, 14:50
14,730
-22
6 Nov 2026, 15:18
14,752
-28
5 Nov 2026, 11:50
14,780
-26
4 Nov 2026, 12:56
14,806
-457
3 Nov 2026, 09:28
15,263
-641
2 Nov 2026, 11:59
15,904
-19
1 Nov 2026, 11:07
15,923
-32
31 Oct 2026, 10:07
15,955
-84
30 Oct 2026, 07:30
16,039
-225
29 Oct 2026, 10:30
16,264
-26
28 Oct 2026, 08:26
16,290
-20
27 Oct 2026, 11:36
16,310
-24
26 Oct 2026, 14:16
16,334
-19
25 Oct 2026, 12:06
16,353
-27
24 Oct 2026, 13:18
16,380
-20
23 Oct 2026, 15:10
16,400
-21
22 Oct 2026, 18:28
16,421
first reading
Engagement
71 posts held, back to 12 April 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 74 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
0.167%
avg views ÷ 14,427 subscribers
Avg views / post
24.2
44 posts measured
Reaction rate
81.5%
reactions ÷ views · ER floor
Posts in window
44
of 71 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. It is computed over the 13 of 44 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 12 November 2026
Posts held
71 (12 April 2026 – 12 November 2026)
Views total
1,063
Reactions total
711
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
13 Nov 2026, 07:45 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.
What this channel posts
Photos
88
Videos
13
Links
26
Lifetime counters from Telegram’s own channel header, read 13 November 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
2m 36s
Average length
14s
Measured directly from 11 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
1,764 reactions across 31 posts, in 12 distinct kinds. The most used accounts for 14.2% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🎉
251
14.2%
❤
241
13.7%
🔥
223
12.6%
👍
215
12.2%
🥰
192
10.9%
👏
147
8.33%
😁
122
6.92%
🤩
104
5.90%
💯
102
5.78%
❤🔥
83
4.71%
😍
83
4.71%
🤣
1
0.057%
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 32 of the 71 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 1,764 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 71 most recent posts we hold, published 12 April 2026 to 12 November 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
Telegram’s own ‘edited’ marker: 6 of 44 posts held from the last 30 days (13.6%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
✨Осенняя фотосессия с белым конём ✨
Нежный атмосферный кадр в осеннем тумане: белое пальто, длинные волосы, красивый белый конь и естественная эстетика случайного фото на iPhone.
💚💙🩷💚💚💚⬇️
🌸🌸🌸
SEED 777777. Фотореалистичное вертикальное фото 9:16 на iPhone, без вспышки. Используй загруженное фото как единственный источник внешности, сохрани лицо и все индивидуальные черты на 100%.
Девушка стоит рядом с красивым бел…
🎀Ночная поездка: поймать момент 🎀
Создаём атмосферный случайный кадр из ночной поездки: развевающиеся волосы, огни города и та самая эстетика старых фотографий без фильтров и обработки.
🌸🔤🔤🔤🔤🔤🔤🌿
⬇️⬇️
Вертикальное фотореалистичное фото 9:16, случайный ночной снимок на старый iPhone 5. Используй загруженное фото как единственный источник внешности, сохрани лицо, черты и пропорции тела без изменений.
Девушка высунул…
До и после: одно преображение — два совершенно разных образа 📸
🌸🌸🌸
Хочешь получить глянцевый снимок в стиле Canon PowerShot G7 X Mark III? С выразительным макияжем, бронзовым сиянием кожи, эффектом прямой вспышки и роскошным вечерним образом?
🔤🔤🔤🔤🔤🔤🔥👇
⭐️⭐️
ULTRA REALISTIC CANON POWERSHOT G7 X MARK III PHOTO, SEED 777777, VERTICAL 3:4. Используй загруженное фото как единственный источник внешности, сохрани лицо и …
🔴Зимняя эстетика: сэлфи под падающим снегом🔴
Хочешь получить атмосферное ночное фото со снегом, роскошной шубой и эффектом живого кадра? 📱
💚💙🩷💚💚💚👇👇👇
👇👇👇
Используй загруженное фото как референс. Максимально точно сохрани все черты лица, индивидуальность и внешность человека.
Создай фотореалистичное ночное селфи на фронтальную камеру iPhone 17, без телефона в кадре. Съёмка под углом, кадр слегка наклонён по диагона…
🚩А если бы твоя жизнь превратилась в видеоигру?🚩
➡️➡️➡️
Преврати обычную фотографию в стильный ретро-постер! Сверху останется оригинальный снимок, а снизу появится его пиксельная версия в стиле старых 16-битных игр.
💚💙🩷💚💚💚👇👇👇👇👇
🔥🔥🔥
Преврати загруженную фотографию в стильный вертикальный постер формата 3:4, разделённый на две абсолютно равные горизонтальные части.
Верхняя часть:
Оставь оригинальную фотографию без …
🩶🩶Один окурок — и сцена из голливудского боевика!
⭐️🔤🔤🔤🔤🔤🔤⭐️👇
📢📢
Мужчина уверенно идёт по ночной освещённой трассе и бросает окурок вверх и назад через плечо. Окурок пролетает над его головой, описывает дугу и падает на асфальт позади него. В момент первого касания земли происходит мощный взрыв с яркой вспышкой, разлетающимися искрами, огромным огненным шаром и густым дымом.
Камера непрерывно отъезжает назад, посте…
😍Два лица, один кадр: эстетика чёрно-белой fashion-фотографии
👆👆👆
Эффектная фотосессия для двоих, будто кадр из модного журнала. Экстремально крупный план, глубокие тени, выразительные взгляды и никакой искусственной ретуши.
⭐️🔤🔤🔤🔤🔤🔤⭐️👇
🩷🩷🩷
Используй прикреплённые фотографии девушки и мужчины как строгий референс внешности. Не меняй их лица, черты лица, возраст и причёски. Создай максимально фотореалистичный вертика…
🖤 Тёмная эстетика: фото, в котором главное — взгляд
👇👇
Минимум света, глубокие тени, чёрный капюшон и выразительные глаза. Получается загадочный кадр с атмосферой ночной фотосессии.
📸 💚💙🩷💚💚💚⬇️⬇️⬇️
🎀🎀🎀🎀🎀🎀🎀🎀
Не меняя внешности человека с загруженного фото, создай фотореалистичный портрет в формате 9:16. Девушка лежит на кровати, камера расположена очень близко к лицу. На ней чёрное худи с капюшоном, который почти полн…
🖤 Селфи, которое выглядит как кадр из дорогой фотосессии
🔴🔴🔴
Иногда для красивого снимка не нужна студия, фотограф и сложная обработка — достаточно удачного ракурса и правильного промпта.
📸 💚💙🩷💚💚💚⬇️⬇️⬇️
🩷
Чёрно-белое фотореалистичное селфи 9:16, снятое на фронтальную камеру iPhone 16 Pro Max. Девушка лежит на светлой смятой простыне, камера строго сверху. В кадре видна половина лица, один глаз смотрит прямо в объект…
🤪 Ночная поездка в Москва-Сити: кадр, будто из фильма
🔗
Иногда один снимок может передать целую историю — ночной город, дорогие автомобили, приглушённый красный свет и момент, пойманный случайно.
📸 💚💙🩷💚💚💚⬇️⬇️⬇️
🩶
Создай фотореалистичное кинематографичное фото в формате 3:4. Сцена снята из салона автомобиля через лобовое стекло во время ночной поездки по трассе в сторону Москва-Сити. В верхней части кадра видно зерка…
🖤Когда один взгляд говорит больше тысячи слов
🌿 Хочешь необычную чёрно-белую фотографию с атмосферой загадочной fashion-съёмки? Попробуй создать такой кадр с помощью ИИ.
📸 💚💙🩷💚💚💚⬇️⬇️⬇️
🎀🎀🎀🎀
Создай фотореалистичное чёрно-белое фото 9:16, сохранив внешность девушки и парня с референсов без изменений.
Девушка стоит спиной к камере, слегка повернув голову через левое плечо. На ней облегающее чёрное платье на тонких бре…
❄️ СОЗДАЙ ОБРАЗ КАК У МОДЕЛИ VOGUE
Зимняя fashion-съёмка в стиле дорогого глянца теперь доступна без фотографа, стилиста и аренды студии!
✨Промпт для генерации:✨
🔵🔵🔵
«Создай профессиональную зимнюю fashion-фотосессию: девушка в роскошной светлой меховой шубе, высоких сапогах и стильной меховой шапке стоит на заснеженной улице европейского города. Эстетика Vogue, дорогой образ, кинематографичный свет, максимальный ф…
Showing the 12 most recent of 71 posts we hold for @okigpt. 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.
Forward network
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.
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 12 November 2026 — this
entry's latest reading, not the date you are reading this.
“Oki GPT (ChatGPT, Kling, Nano Banana, Suno и др.)” (@okigpt), 14,427 subscribers as measured 12 November 2026. Telegram Register, tgregister.com/channel/okigpt.
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.