Memes & entertainment — 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 82% 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 4 other registered channels. This entry also forms a group of 2 channels linked by matching posts. 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 (6 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. 11 of the 11 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 139 comparable posts for this entry, running 29 July 2026 to 23 September 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).
Of the group of 2 channels, the one whose matching posts we hold earliest is @sabiasque — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the keys clone_mutual · clone_source, last confirmed 12 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.
Channels linked by matching posts
This channel is in a group of 2 registered channels linked by matching posts. Links are found by comparing text fingerprints across every channel on the register.
Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
290 measurements spanning 98 days, net -126,426. 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 18,562–182,916 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 290
Measured (UTC)
Subscribers
Change
12 Nov 2026, 07:40
37,526
-1
11 Nov 2026, 15:08
37,527
no change
11 Nov 2026, 14:56
37,527
-2
11 Nov 2026, 06:46
37,529
-9
10 Nov 2026, 23:46
37,538
-13
10 Nov 2026, 03:21
37,551
no change
9 Nov 2026, 22:39
37,551
no change
9 Nov 2026, 22:17
37,551
-2
9 Nov 2026, 15:36
37,553
-5
9 Nov 2026, 09:41
37,558
-8
8 Nov 2026, 17:47
37,566
-1
8 Nov 2026, 14:58
37,567
-1
8 Nov 2026, 10:15
37,568
-1
8 Nov 2026, 07:48
37,569
-2
7 Nov 2026, 22:11
37,571
-10
7 Nov 2026, 12:57
37,581
no change
7 Nov 2026, 10:39
37,581
-2
7 Nov 2026, 04:11
37,583
no change
7 Nov 2026, 03:47
37,583
+5
6 Nov 2026, 19:16
37,578
first reading
Engagement
154 posts held, back to 29 July 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 100 pages 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 154 posts for this entry, the most recent from 23 September 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
31m 28s
Average length
30s
Measured directly from 64 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
50,323 reactions across 153 posts, in 53 distinct kinds. The most used accounts for 24.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
12,504
24.8%
👍
9,167
18.2%
🤣
8,572
17.0%
🤯
4,093
8.13%
😱
2,371
4.71%
👏
2,148
4.27%
🥴
1,784
3.55%
✍
1,184
2.35%
👀
1,039
2.06%
🤪
955
1.90%
😁
901
1.79%
🔥
899
1.79%
🥰
662
1.32%
😢
585
1.16%
😨
460
0.914%
🗿
356
0.707%
🍌
290
0.576%
🤩
248
0.493%
👌
225
0.447%
🫡
219
0.435%
33 further kinds
1,661
3.30%
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 153 of the 154 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 50,323 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 154 most recent posts we hold, published 29 July 2026 to 23 September 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.
¿Sabías qué?... En Japón, han comenzado a desarrollar casas-robots donde las personas no tendrán que preocuparse por las tareas domésticas.
La inteligencia artificial supervisará lo que ocurre en la casa, realizará tareas de limpieza, organizará los alimentos, lavará la ropa y llevará a cabo otras tareas domésticas.
El proyecto ha recibido apoyo gubernamental y se planea su producción en masa.
Únete a 🤩 @sabiasque…
¿Sabías qué?... El “Terminator” golpeó brutalmente a un vlogger dentro de la jaula y le rompió la muñeca.
Frankie LePenna se enfrentó a un robot de combate en un torneo al estilo de Real Steel y recibió un par de golpes contundentes.
Ni siquiera un chaleco protector pudo evitar la lesión.
Únete a 🤩 @sabiasque en Telegram
¿Sabías qué?... En San Petersburgo, un motociclista sufrió un accidente a 300 km/h y sobrevivió milagrosamente.
El conductor había alcanzado una velocidad vertiginosa cuando su mochila fue succionada por la rueda trasera. La rueda se bloqueó, haciendo que el motociclista saliera despedido y se deslizara una larga distancia por el asfalto.
A pesar de ello, salió ileso salvo por algunos rasguños, ni siquiera necesitó…
📸 El fotógrafo capturó imágenes increíbles
Una ardilla "ninja" realiza un salto asombroso.
❤️ - Sorprendente
🔥 - No lo sabía
Únete a 🤩 @sabiasque en Telegram
¿Sabías qué?... Se transplantaron neuronas humanas a ratones: después de tres meses, hasta el 90% del tejido cortical estaba compuesto por células humanas
Los ratones se comportaron normalmente, pero su cerebro reaccionó de manera inusual a la falta de oxígeno, casi como el cerebro de un bebé.
El experimento se detuvo por temor a que los ratones pudieran desarrollar signos de conciencia.
Da miedo, apaga 😢.
Únete …
¿Sabías qué?... La pareja de equinos más insólita del mundo, el caballo más alto y el más bajo del planeta, ha entrado en el Libro Guinness de los Récords.
Hugo, un ejemplar británico de cuatro años, alcanzó los 199 cm de altura, mientras que el poni alemán Pumuckel llegó a medir tan solo 52,6 cm.
Elige a tu luchador.
Únete a 🤩 @sabiasque en Telegram
¿Sabías qué?... Un consolador de 44 cm perforó el intestino de un hombre y llegó hasta su hígado.
Un hombre japonés terminó en el hospital tras una velada romántica con su pareja. Una tomografía computarizada reveló que el juguete había perforado la pared intestinal, dejando un orificio de aproximadamente 5 cm.
El paciente fue sometido a una cirugía de urgencia y puesto en coma inducido; recibió el alta tres semana…
¿Sabías qué?... Se ha instalado un simulador de parto en un festival juvenil en Ekaterimburgo.
Cualquier persona interesada puede sentarse en la silla, conectarse a la máquina y experimentar sensaciones que imitan las contracciones del parto.
La atracción está resultando especialmente popular entre los hombres jóvenes, mientras que las mujeres ya piden en los comentarios que se instale uno en cada ciudad.
Únete a …
¿Sabías qué?... Los alumnos de primer grado están demostrando ser incapaces de realizar tareas básicas de autocuidado debido al fenómeno de la “mamá beige”, no saben vestirse, atarse los cordones ni siquiera usar el baño.
Los maestros se encuentran cada vez más con situaciones en las que los alumnos carecen por completo de habilidades para la vida cotidiana.
Por ejemplo, una madre pidió a una maestra que “le limpia…
¿Sabías qué?... El cerebro de la mosca muerta ha sido convertida en el operador de un dron FPV. Ya sabe cómo evitar obstáculos y mantener el dron a baja altura.
Estamos perdidos😭.
Únete a 🤩 @sabiasque en Telegram
¿Sabías qué?... Un hombre violó un pez en video, la impactante historia del tailandés que abusaba de peces se convierte en noticia.
Un hombre de 51 años entró al agua y abusó de un pobre pez. El dueño de la víctima lo vio y persiguió al amante de los peces, pero este escapó.
Más tarde, durante el interrogatorio, confesó que no tenía dinero para una mujer, y que el pez “nadaba muy bien”, y así comenzó todo...
Únete…
🤯184🤣78😱50😁27❤25💊20🌚8🗿4
Showing the 12 most recent of 154 posts we hold for @sabiasque. 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 recorded as deleted after publishing
We recorded 4 posts on @sabiasque 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
16 August 2026
Median time before seen missing
28 hours
Seen missing in the last 30 days
0
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 15 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.
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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 12 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
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.
💡CURIOSAMENTE🧠 @curiosamenteee · 22,810 Telegram ranks this channel #1 of 68 here — alongside 67 others — read 18 September 2026
ATRACCIÓN MENTAL🧠 @atraccionmental · 25,839 Telegram ranks this channel #1 of 66 here — alongside 65 others — read 12 September 2026
Sabias que? @sabiasqueoficial · 37,526 Telegram ranks this channel #1 of 74 here — alongside 73 others — read 31 August 2026
Cosas que no sabías💡 @curiosidadesss · 50,738 Telegram ranks this channel #1 of 80 here — alongside 79 others — read 25 August 2026
MUNDO FITNESS🏋🏻♂️💪 @Mundo_Fitness · 22,780 Telegram ranks this channel #4 of 63 here — alongside 62 others — read 18 September 2026
Noticias 24 horas @Noticias24horasTelegram · 101,560 Telegram ranks this channel #4 of 76 here — alongside 75 others — read 17 August 2026
Buzz💡 Datos interesantes @buzzdatos · 117,948 Telegram ranks this channel #4 of 83 here — alongside 82 others — read 13 August 2026
Buzz 👨🏫 Quiz @buzzquizzes · 21,909 Telegram ranks this channel #5 of 80 here — alongside 79 others — read 19 September 2026
📺 Zona Seriéfilos HD 📺 @SeriesClubHD · 24,198 Telegram ranks this channel #5 of 49 here — alongside 48 others — read 18 September 2026
XROMOSOMA EXTRA @xromosoma_extra · 30,622 Telegram ranks this channel #5 of 66 here — alongside 65 others — read 5 September 2026
Buzz 💬 Citas @buzzcitas · 60,957 Telegram ranks this channel #5 of 82 here — alongside 81 others — read 21 August 2026
Happy Wellness @bienestar · 24,921 Telegram ranks this channel #6 of 74 here — alongside 73 others — read 14 September 2026
Soyuz 📚 Historia @SoyuzHistoria · 56,538 Telegram ranks this channel #6 of 75 here — alongside 74 others — read 22 August 2026
✏️ NUEVAS PALABRAS 📓 @Diccionarioletras · 23,905 Telegram ranks this channel #7 of 72 here — alongside 71 others — read 16 September 2026
TEMAS TGM @TemasTGM · 25,526 Telegram ranks this channel #7 of 56 here — alongside 55 others — read 12 September 2026
📚 DATOS CURIOSOS 🔍 @DatosCuriosos · 31,559 Telegram ranks this channel #7 of 76 here — alongside 75 others — read 5 September 2026
Memes Latinos ® @memesltn · 33,682 Telegram ranks this channel #7 of 66 here — alongside 65 others — read 2 September 2026
Crónica Policial @cronicaspoliciales · 83,455 Telegram ranks this channel #10 of 60 here — alongside 59 others — read 4 September 2026
películas y series 🍿 @peliculas · 472,753 Telegram ranks this channel #12 of 52 here — alongside 51 others — read 24 August 2026
Actualidad Oscura @actualidadoscura · 102,599 Telegram ranks this channel #13 of 44 here — alongside 43 others — read 4 September 2026
Fitness Living® @FitnessLiving · 29,142 Telegram ranks this channel #14 of 49 here — alongside 48 others — read 12 September 2026
¡Hay que verlo! @hayqverlo · 23,326 Telegram ranks this channel #15 of 82 here — alongside 81 others — read 17 September 2026
Buzz 📚 Historia @buzzhistoria · 73,607 Telegram ranks this channel #15 of 80 here — alongside 79 others — read 19 August 2026
APRENDE INGLÉS 🇬🇧🇺🇸 @aprendeinglesfree · 22,769 Telegram ranks this channel #17 of 52 here — alongside 51 others — read 19 September 2026
This channel appears in 151 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. 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 12 November 2026 — this
entry's latest reading, not the date you are reading this.
“Sabias que?” (@sabiasque), 37,526 subscribers as measured 12 November 2026. Telegram Register, tgregister.com/channel/sabiasque.
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.
