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Channel

Lexy | Промты • ИИ • Новости

@lexygpt

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Posts edited after publishing · Citations · Cite this entry

199,910subscribers

-1,293 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 100,000–316,228.

Register entry

Telegram ID-1002421757799
TypeChannel
Username@lexygpt
DescriptionСоздаю премиум-портреты из ваших фото. Как после съемки у топ-фотографа ✨ Попробуй: https://t.me/lexygpt_bot?start=NEWS_ref0 Поддержка: @lexygpt_support
CreatedBetween 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live25 September 2026
Measurements held33
Confirmed unchanged1 time, most recently 25 September 2026
On Telegramt.me/lexygpt

Topic

Technology — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 8 August 2026 and assigned it the closest of 31 fixed categories, at 73% 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

199,842201,203200,522.57 August 2026 — 201,203 subscribers8 August 2026 — 201,175 subscribers9 August 2026 — 201,104 subscribers10 August 2026 — 201,044 subscribers11 August 2026 — 200,975 subscribers12 August 2026 — 200,892 subscribers13 August 2026 — 200,820 subscribers14 August 2026 — 200,737 subscribers16 August 2026 — 200,699 subscribers17 August 2026 — 200,660 subscribers18 August 2026 — 200,642 subscribers19 August 2026 — 200,598 subscribers20 August 2026 — 200,569 subscribers21 August 2026 — 200,514 subscribers22 August 2026 — 200,516 subscribers24 August 2026 — 200,405 subscribers25 August 2026 — 200,302 subscribers26 August 2026 — 200,169 subscribers27 August 2026 — 200,148 subscribers28 August 2026 — 200,048 subscribers29 August 2026 — 199,960 subscribers30 August 2026 — 199,942 subscribers1 September 2026 — 199,879 subscribers2 September 2026 — 199,913 subscribers3 September 2026 — 199,849 subscribers5 September 2026 — 199,842 subscribers8 September 2026 — 199,932 subscribers11 September 2026 — 199,949 subscribers13 September 2026 — 200,054 subscribers15 September 2026 — 200,036 subscribers16 September 2026 — 199,998 subscribers19 September 2026 — 199,955 subscribers25 September 2026 — 199,910 subscribers199,9107 August 202625 September 2026
33 measurements spanning 49 days, net -1,293. 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 199,638–201,407 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 33
Measured (UTC)SubscribersChange
25 Sept 2026, 20:20199,910-45
19 Sept 2026, 04:21199,955-43
16 Sept 2026, 22:01199,998-38
15 Sept 2026, 00:21200,036-18
13 Sept 2026, 09:02200,054+105
11 Sept 2026, 12:18199,949+17
8 Sept 2026, 15:59199,932+90
5 Sept 2026, 12:57199,842-7
3 Sept 2026, 14:37199,849-64
2 Sept 2026, 04:15199,913+34
1 Sept 2026, 01:38199,879-63
30 Aug 2026, 21:56199,942-18
29 Aug 2026, 19:13199,960-88
28 Aug 2026, 19:45200,048-100
27 Aug 2026, 22:58200,148-21
26 Aug 2026, 19:44200,169-133
25 Aug 2026, 18:36200,302-103
24 Aug 2026, 15:46200,405-111
22 Aug 2026, 21:44200,516+2
21 Aug 2026, 15:07200,514first reading

Engagement

354 posts held, back to 6 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 114 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
4.70%
avg views ÷ 199,910 subscribers
Avg views / post
9,400
192 posts measured
Reaction rate
0.222%
reactions ÷ views · ER floor
Posts in window
192
of 354 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 1 October 2026
Posts held354 (6 August 2026 – 1 October 2026)
Views total1,805,670
Reactions total4,011
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken1 Oct 2026, 20:52 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
≈3,230
Videos
≈197
Links
≈1,270

Lifetime counters from Telegram’s own channel header, read 1 October 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Video runtime
8m 32s
Average length
13s

Measured directly from 40 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

7,465 reactions across 354 posts, in 17 distinct kinds. The most used accounts for 53.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤4,00453.6%
🔥1,00613.5%
😍74710.0%
❤‍🔥6849.16%
🥰4936.60%
👍1942.60%
🤩730.978%
💘680.911%
😎470.63%
👏380.509%
🤪350.469%
😱260.348%
💔180.241%
😇160.214%
😈70.094%
🙏50.067%
🎉40.054%

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 354 of the 354 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 7,465 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 354 most recent posts we hold, published 6 August 2026 to 1 October 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.

Telegram Stars

Stars received
14
across the posts below
Posts paid on
14
of 354 we hold a reading for · 4%
Most on one post
1
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @lexygpt. 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 354 most recent posts we hold for this entry, published 6 August 2026 to 1 October 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.

Recent posts

1 Oct 2026, 18:02 UTC≈2,670 views9 reactionsread 1 October 2026
Forwarded from @lexygpt_trendsVideo

Этот трек нашел тебя 🔥 Когда ты не пытаешься быть в центре внимания — ты просто им являешься. Повтори вирусный тренд с турецким вайбом. #женский@lexygpt_trends #мужской@lexygpt_trends

🔥3❤2❤‍🔥2😱2

1 Oct 2026, 17:02 UTC≈3,530 views5 reactionsread 1 October 2026
Photo

Эффектный мужской фотосет в бильярдном клубе 🖤 Живые кадры в атмосферной локации, которые создают уверенный образ Сделать очень просто: загрузите свое портретное фото и получите готовые кадры ✨ Посмотреть остальные фотосеты

❤‍🔥3🔥1😎1

1 Oct 2026, 15:28 UTC≈4,270 views5 reactionsread 1 October 2026
Photo

Расслабленные фотографии дома 🤍 1️⃣Переходи в бот и включай модель Nano Banana 2.0 — @lexygpt_bot 2️⃣Отправляй качественное фото, где чётко видны пропорции лица 3️⃣Перед отправкой добавляй промт в описание (копируй текст одним касанием 👇): Кадр 1: СТРОГО сохранить внешность 1:1 — лицо, черты, пропорции, текстуру кожи, тон кожи, возраст, цвет и длину волос, цвет глаз с фото. Формат 9:16 Женщина сидит на диване. Она …

❤2🥰2😍1

1 Oct 2026, 13:28 UTC≈5,210 views11 reactionsread 1 October 2026
Photo

Уютные осенние фото с кофе у витрины пекарни 🍪 1️⃣Переходи в бот и включай модель Nano Banana 2.0 — @lexygpt_bot 2️⃣Отправляй качественное фото, где чётко видны пропорции лица 3️⃣Перед отправкой добавляй промт в описание (копируй текст одним касанием 👇): Кадр 1: СТРОГО сохранить внешность человека 1:1 — лицо, черты, пропорции, телосложение, тон кожи, возраст, цвет и длину волос. Формат 9:16. Реалистичная уютная осе…

❤6💘2🔥2👍1

1 Oct 2026, 11:29 UTC≈5,840 views7 reactionsread 1 October 2026
Photo

Задумчивый кадр в поле 🤍 Как повторить такое фото: 1️⃣Нажимай кнопку «повторить» 2️⃣Отправляй качественное фото, где хорошо видны черты лица #женский@lexygpt #одиночный@lexygpt

❤5🥰1😍1

1 Oct 2026, 09:28 UTC≈6,530 views11 reactionsread 1 October 2026
Photo

Серия кадров в зеркале 🤎 1️⃣Переходи в бот и включай модель Nano Banana 2.0 — @lexygpt_bot 2️⃣Отправляй качественное фото, где чётко видны пропорции лица 3️⃣Перед отправкой добавляй промт в описание (копируй текст одним касанием 👇): Кадр 1: СТРОГО сохранить внешность 1:1 — лицо, черты, пропорции, текстура кожи, тон кожи, возраст, цвет и длину волос. Формат: 9:16. делает селфи в зеркале. У нее волосы, собранные в …

❤7🔥2🥰2

1 Oct 2026, 07:28 UTC≈7,190 views14 reactionsread 1 October 2026
Photo

Серия атмосферных фото в образе девушки - кошки 🖤 1️⃣Переходи в бот и включай модель Nano Banana 2.0 — @lexygpt_bot 2️⃣Отправляй качественное фото, где чётко видны пропорции лица 3️⃣Перед отправкой добавляй промт в описание (копируй текст одним касанием 👇): Кадр 1: СТРОГО сохранить внешность 1:1 — лицо, черты, пропорции, текстура кожи, тон кожи, возраст, цвет и длину волос. Формат: 9:16. женщина одетая в черный не…

❤8❤‍🔥3🔥2😍1

30 Sept 2026, 18:01 UTC≈8,740 views8 reactionsread 1 October 2026
Forwarded from @lexygpt_trendsVideo

Ночная гонка под дождём 🏁 Мокрая дорога, свет фонарей на асфальте, окно опускается — и взгляд прямо в камеру. Вспышка из выхлопной, и машина растворяется в темноте. Реалистичное видео от первого лица, будто снятое на телефон из соседней машины. Сделать очень просто: загрузите ваши фото и получите готовое видео #женский@lexygpt_trends

❤5🤩2🔥1

30 Sept 2026, 17:02 UTC≈8,300 views6 reactionsread 1 October 2026
Photo

Стильный мужской фотосет в городе на пленку 🏙 Атмосферные городские кадры, которые создают ощущение дорогого кино Сделать очень просто: загрузите свое портретное фото и получите готовые кадры ✨ Посмотреть остальные фотосеты

❤4🔥1😎1

30 Sept 2026, 15:28 UTC≈8,610 views12 reactionsread 1 October 2026
Photo

Романтичные парные кадры со свадебного банкета 🥂 1️⃣Переходи в бот и включай модель Nano Banana 2.0 — @lexygpt_bot 2️⃣Отправляй качественное фото, где чётко видны пропорции лица 3️⃣Перед отправкой добавляй промт в описание (копируй текст одним касанием 👇): Кадр 1: СТРОГО сохранить внешность главного человека 1:1 — лицо, черты, пропорции, телосложение, тон кожи, возраст, цвет и длину волос. Формат 9:16. Реалистичная…

❤‍🔥5🔥3❤2😍2

30 Sept 2026, 13:28 UTC≈8,960 views11 reactionsread 1 October 2026
Photo

Серия стильных кадров в современном лифте 💄 1️⃣Переходи в бот и включай модель Nano Banana 2.0 — @lexygpt_bot 2️⃣Отправляй качественное фото, где чётко видны пропорции лица 3️⃣Перед отправкой добавляй промт в описание (копируй текст одним касанием 👇): Кадр 1: СТРОГО сохранить внешность человека 1:1 — лицо, черты, пропорции. Формат 9:16. Реалистичный крупный портрет человека в современном закрытом лифте из матовой н…

❤7🔥2🤩2

30 Sept 2026, 11:28 UTC≈9,320 views22 reactionsread 1 October 2026
Photo

Серия утонченных студийных портретов 🤍 1️⃣Переходи в бот и включай модель Nano Banana 2.0 — @lexygpt_bot 2️⃣Отправляй качественное фото, где чётко видны пропорции лица 3️⃣Перед отправкой добавляй промт в описание (копируй текст одним касанием 👇): Кадр 1: СТРОГО сохранить внешность 1:1 — лицо, черты, пропорции, текстура кожи, тон кожи, возраст, цвет и длину волос. Формат 9:16. Чёрно-белый студийный фэшн-портрет в по…

❤17🥰3❤‍🔥2

Showing the 12 most recent of 354 posts we hold for @lexygpt. 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.

Posts edited after publishing

@lexygpt edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.

An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.

First edit seen
4 September 2026
Most recent edit
4 September 2026

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.

Mentions

Named by 3 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.

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 25 September 2026 — this entry's latest reading, not the date you are reading this.

“Lexy | Промты • ИИ • Новости” (@lexygpt), 199,910 subscribers as measured 25 September 2026. Telegram Register, tgregister.com/channel/lexygpt.

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.