Gaming — 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 100% 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.
Content that also appears on other registered channels
Posts published here appear in near-verbatim form on 1 other registered channel. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.
Matching posts — open both and compare (5 of the pairs behind the counts below)
Channels this entry shares post bodies with, where at least one matching post pair has no forward credit between the two channels, or to a common source, recorded in our data
Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.
What this cannot establish
MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.
Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 4 of the 5 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.
“Published first” means first in this corpus. We hold 278 comparable posts for this entry, running 4 August 2026 to 10 November 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.
The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.
Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).
Views per post sit far below this size band
65.8 average views per post against 14,113 subscribers — an engagement rate of 0.467%. 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
26 of 26 published in the window (26 exact, 0 rounded by Telegram)
Views totalled
1,712
Mature posts only
0.547% over 16 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 keys clone_copy · err_low, last confirmed 11 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 96 days, net -531. 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 14,001–14,692 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 65
Measured (UTC)
Subscribers
Change
10 Nov 2026, 13:57
14,081
-9
9 Nov 2026, 01:10
14,090
-9
7 Nov 2026, 20:45
14,099
-8
6 Nov 2026, 22:07
14,107
-2
5 Nov 2026, 20:07
14,109
-4
4 Nov 2026, 19:30
14,113
-5
3 Nov 2026, 19:58
14,118
-8
2 Nov 2026, 21:30
14,126
-2
2 Nov 2026, 00:17
14,128
-1
1 Nov 2026, 01:47
14,129
-8
31 Oct 2026, 04:11
14,137
-7
30 Oct 2026, 01:41
14,144
-16
29 Oct 2026, 03:07
14,160
-15
28 Oct 2026, 04:27
14,175
-9
27 Oct 2026, 03:11
14,184
-4
26 Oct 2026, 05:16
14,188
-12
25 Oct 2026, 05:17
14,200
-3
24 Oct 2026, 07:25
14,203
-6
23 Oct 2026, 07:04
14,209
-9
22 Oct 2026, 03:39
14,218
first reading
Engagement
321 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 90 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
0.543%
avg views ÷ 14,081 subscribers
Avg views / post
76.4
69 posts measured
Reaction rate
—
this channel exposes no reaction counts
Posts in window
69
of 321 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 11 November 2026
Posts held
321 (4 August 2026 – 11 November 2026)
Views total
5,272
Reactions total
—
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
11 Nov 2026, 13:39 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
≈13,200
Videos
≈6,620
Links
≈10,100
Lifetime counters from Telegram’s own channel header, read 11 November 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
1h 41m
Average length
30s
Measured directly from 204 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.
Recent posts
Telegram’s own ‘edited’ marker: 26 of 69 posts held from the last 30 days (37.7%) 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).
💘 Reel Ai — ᴦᴇнᴇᴩᴀция ʙидᴇᴏ и ɸᴏᴛᴏ ᴨᴩяʍᴏ ʙ Tᴇlᴇgrᴀʍ
Зᴀᴦᴩужᴀᴇɯь ɸᴏᴛᴏ → ʙыбиᴩᴀᴇɯь ᴩᴇжиʍ иᴧи ᴨиɯᴇɯь ᴄʙᴏй ᴄцᴇнᴀᴩий → ᴨᴏᴧучᴀᴇɯь ᴩᴇɜуᴧьᴛᴀᴛ ʙ ᴧичᴋу
🔞 Оᴋᴏᴧᴏ 1000 ᴩᴇжиʍᴏʙ дᴧя ɸᴏᴛᴏ и ʙидᴇᴏ
♾ Пᴩᴏдᴧᴇниᴇ ᴦᴏᴛᴏʙᴏᴦᴏ ʙидᴇᴏ дᴏ бᴇᴄᴋᴏнᴇчнᴏᴄᴛи
🔗 Гᴏᴛᴏʙыᴇ ᴄюжᴇᴛы и цᴇᴨᴏчᴋи иɜ ᴩᴀɜных ᴩᴇжиʍᴏʙ
🔞 И это лишь малая часть того, что можно создать. В самом приложении тебя ждут куда более смелые возможности 😈
👇ПЕРЕЙТИ В ПРИЛОЖЕНИЕ👇
r/
Это кот по кличке Маури, который очень любит огурцы
Более того, он способен за считаные секунды найти огурец среди множества цукини!
Oculus Inferno
LIVE 🟧🟧🟧🟧🟧🟧🟧🟧
⏺ Прямой эфир всего спорта, пользуйся: @LiveGoal_bot 👍
LIVE 🟧🟧🟧🟧🟧🟧🟧🟧
Ким Чен Ын впал в кому после кровоизлияния в мозг и был экстренно госпитализирован в одну из больниц Пекина, сообщает издание The Sun. Официального подтверждения этой информации пока нет.
В последний раз лидера КНДР видели на публике 11 октября.
r/
Oculus Inferno
Даша Дошик 🔞
сисястая создала 18+ npuватky с д0маwkoй и соло видео с дилдо, все для вас без цензуры 🔥
ВЕСЬ КОНТЕНТ ТУТ👇🔞
https://t.me/+zkJflcQyJ-IxYzI1
https://t.me/+zkJflcQyJ-IxYzI1
3аебался дрочить на обычное порно?🌟
Взято из: В САЛФЕТКУ🧻
Канал для самых извращенных.
Вп%ски, сливы, жесткая ебля, мамки все это ты найдешь тут 👇
🔞Смотреть ФУЛЛЫ без цензуры - https://t.me/+JelYFqNv9T1kZDgy
r/
Американское мороженое не тает под горячей водой
Всё дело в стабилизаторах, которые связывают воду и создают внутренний каркас. Также часто производители используют растительные жиры вместо молочных — у них другая температура плавления.
В результате многие десерты с таким составом даже нельзя назвать мороженым — только «замороженным молочным десертом».
Oculus Inferno
✍️✍️✍️✍️Больше контента💦 - https://t.me/+…
r/
Около 250 человек собрались в Чикаго, чтобы сдвинуть знаменитую скульптуру, которую жители прозвали «фасолиной», на 18 сантиметров влево
Затея связана с давней конспирологией: якобы внутри скульптуры застрял человек, а под ней есть потайная дверь. Если немного сдвинуть «фасоль», ему можно будет передать еду и другие припасы.
В итоге 110-тонная конструкция даже не шелохнулась.
Oculus Inferno
r/
Во Флориде самолет сел прямо на трассу, зацепив проезжающий пикап
Пилоты приняли решение об экстренной посадке из-за возникших в воздухе технических неполадок и мастерски вписались в едущий поток, слегка поцарапав кузов автомобиля.
Oculus Inferno
В США корги чуть не сорвал матч по американскому футболу, выбежав на поле.
На поимку пса бросились сразу несколько сотрудников стадиона, но тот ловко от них уворачивался.
r/
Oculus Inferno
🥹☺️😉😗😝🤓😏😀
1. 📍 ПРОДОЛЖЕНИЕ
2. 📍 Нюдсики
3. 📍 XHUMSTER
4. 📍 Домашка
r/
Милота дня: в японском городке Мацуяма открыли заведение, где у всех официанток деменция
Одно из мест временно переименовалось в «Ресторан перепутанных заказов». В этот день всех сотрудников обслуживали пожилые женщины с деменцией. Они постоянно записывали не те блюда, путали заказы и в целом ошибались, но посетители не были против.
С помощью этого мероприятия организаторы хотели нормализовать людей с деменцией,…
r/
Такое точно нужно сделать у нас: китайцы разработали приложение для борьбы с импульсивными покупками
В нём решение о том, нужно ли тратить деньги на покупки принимают друзья, родственники и даже незнакомцы.
Пользователи составляют списки желаемых товаров и отправляют ссылки другим людям. Те голосуют, нужно ли совершать покупку.
Oculus Inferno
🥹☺️😉😗😝🤓😏😀
1. 📍 ПРОДОЛЖЕНИЕ
2. 📍 Нюдсики
3. 📍 XHUMSTER
4. 📍 Домашка
Showing the 12 most recent of 321 posts we hold for @oculus_inferno. 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
@oculus_inferno edited 30 posts 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
8 August 2026
Most recent edit
7 November 2026
Posts recorded as deleted after publishing
We recorded 28 posts on @oculus_inferno as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
7 August 2026
Most recent seen missing
11 November 2026
Median time before seen missing
37 hours
Seen missing in the last 30 days
8
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.
Handles this channel named that no longer answer
Dead references
2
handles named in this channel’s posts, vacant today
Evidenced gone
1
we ourselves saw one of these resolve, at some point
Never seen alive
1
vacant every time we have ever looked
@oculus_inferno named 2 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Evidenced gone
We ourselves saw each of these resolve to a real page at some point before it went vacant — a genuine, evidenced change, not an inference from absence.
@snapchatplus18_bot named in 2 posts, 12 August 2026 – 13 August 2026 · confirmed gone 30 October 2026 (two independent sightings — see how we confirm a dead handle)evidenced
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@oshibkabuka named in 2 posts, 12 August 2026 – 13 August 2026
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.
Я тебя хочу @iwantupronvideosseks · 49,957 Telegram ranks this channel #6 of 38 here — alongside 37 others — read 25 August 2026
Анекдоты 18+ @sexxx_pornohumor_prikoly · 79,457 Telegram ranks this channel #55 of 60 here — alongside 59 others — read 24 August 2026
This channel appears in 2 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 10 November 2026 — this
entry's latest reading, not the date you are reading this.
“Oculus Inferno” (@oculus_inferno), 14,081 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/oculus_inferno.
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.
