Education — 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 10 August 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 word for word 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 (6 of the pairs behind the counts below)
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. None of the 0 matches recorded here fall after that date, so for this entry we cannot say whether any of them carried a credit. The duplication is measured; the absence of attribution is not.
“Published first” means first in this corpus. We hold 13 comparable posts for this entry, running 29 July 2026 to 7 August 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).
Across the whole group of 2, the earliest publisher we hold is @ankushchirimar1 — which is this entry. That is a statement about our reading window, not a claim of authorship.
Recorded under the key clone_source, last confirmed 7 August 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.
Also posting the same content
This channel’s posts match, word for word or near enough, posts on 1 other registered channel, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word 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.
58 measurements spanning 90 days, net +2,941. 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 35,454–39,277 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 58
Measured (UTC)
Subscribers
Change
6 Nov 2026, 00:26
38,836
+137
4 Nov 2026, 23:29
38,699
+82
4 Nov 2026, 02:26
38,617
+27
2 Nov 2026, 22:58
38,590
+20
2 Nov 2026, 00:04
38,570
+26
31 Oct 2026, 21:56
38,544
+18
30 Oct 2026, 23:06
38,526
+15
29 Oct 2026, 20:36
38,511
+20
28 Oct 2026, 22:05
38,491
+38
27 Oct 2026, 22:36
38,453
+37
26 Oct 2026, 22:49
38,416
+31
25 Oct 2026, 21:30
38,385
+43
24 Oct 2026, 18:47
38,342
+48
23 Oct 2026, 15:27
38,294
+68
22 Oct 2026, 14:26
38,226
+38
21 Oct 2026, 06:20
38,188
+48
20 Oct 2026, 02:28
38,140
+32
19 Oct 2026, 01:36
38,108
+50
17 Oct 2026, 23:00
38,058
+37
16 Oct 2026, 23:29
38,021
first reading
Engagement
595 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 168 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
12.5%
avg views ÷ 38,836 subscribers
Avg views / post
4,870
190 posts measured
Reaction rate
0.695%
reactions ÷ views · ER floor
Posts in window
191
of 595 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 189 of 190 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 5 November 2026
Posts held
595 (29 July 2026 – 5 November 2026)
Views total
924,740
Reactions total
6,369
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
5 Nov 2026, 22:14 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
Video runtime
2m 32s
Average length
30s
Measured directly from 5 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
12,567 reactions across 589 posts, in 30 distinct kinds. The most used accounts for 91.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
11,552
91.9%
😭
312
2.48%
🔥
207
1.65%
🙏
141
1.12%
👍
85
0.676%
🤯
43
0.342%
💯
30
0.239%
🆒
20
0.159%
🤩
20
0.159%
👏
19
0.151%
🫡
18
0.143%
❤🔥
15
0.119%
😁
15
0.119%
🍾
14
0.111%
⚡
12
0.095%
🎉
10
0.08%
💋
10
0.08%
👀
9
0.072%
🥰
8
0.064%
🙊
5
0.04%
10 further kinds
22
0.175%
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 589 of the 595 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 12,567 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 595 most recent posts we hold, published 29 July 2026 to 5 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.
Telegram Stars
Stars received
1
across the posts below
Posts paid on
1
of 592 we hold a reading for · 0.2%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @ankushchirimar1. 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 595 most recent posts we hold for this entry, published 29 July 2026 to 5 November 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
Telegram’s own ‘edited’ marker: 41 of 191 posts held from the last 30 days (21.5%) 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).
Suno,
I know you might be feeling to pull an all nighter and complete your syllabus, but trust me, this doesn't work in theory subjects like Audit.
You need to have enough rest to function properly and be at your absolute best during exam time.
So please sleep for now, maybe for few hours and then start afresh in the morning 🙏
You will definitely retain better, Trust me 😊
Ps - Replied to All Doubts on Whatsapp &…
Syllabus Still Pending?
Last Resort Videos (only if unable to self study)
Quick Recap Marathon (Full Syllabus in 8 Hours) - https://youtu.be/Hpb3BPvzPXQ?si=65ZrQvogGbEVsuIH
Maha Smart Marathon (All Tricky Points) - https://youtu.be/kas6zgyc3y8?si=rlpp6wShiatdo0TV
Sab Achha Hoga ❤️
Yes guys!!
Hope your preparation is going in full Zosh!!🤩
Aaj Ka he din hai bhai log - then you have small breather if you are appearing for both groups ❤️ But please Aaj Aaj mehnat karlo 🙏
Kuch nahi yaad aa raha? - Don’t worry exam main sab yaad aajayega ❤️ Important is to keep going !!🙏✨
Btw Slot 3 has started!! What’s your update on “A Category” standards? Have you started with B category?
❤️ LAST DIWALI, WE DID IT. THIS DIWALI, WE’RE DOING IT AGAIN! 🪔
I’ve always believed that no one should be left behind during a festival just because life wasn’t fair to them.
While we celebrate Diwali with new clothes, sweets and lights, there are families still struggling to arrange their next meal. Some children have never even experienced what a joyful Diwali feels like.
This year, with your love and God’s gra…
AFM ke gam se ab bahaar aa jaao 🙏
Slot 2 has already started!
Complete All A Category Standards till 2pm ✌️
React with ❤️ if you accept this challenge!
35 Marks covered in Just 5 Hours Effectively 🔥
27,000+ Views
450+ LIVE Viewers
750+ Likes
Thank you so very much for all the love and trust 🥹❤️
Please share your feedbacks in comments:
https://www.youtube.com/live/Xsd1-WxNuFg?si=FL4eJwh7br7wk5LG
Based on many students request, Recorded version of this video is available on Youtube 😊🙏
Mazza aa gaya ❤️
Iss baar Audit me Pass hone se koi nahi rok sakta humein 💪
J…
CA Final with Ankush Chirimar Classes ♥️ pinned «Everything that you need for Audit ❤️ Pin this channel on Telegram for Next 1.5 Days 🙌 1. Planner for 1.5 Days - https://youtu.be/o79nA6LGHOU?si=157ZJqu2vMdftZz7 2. Exam Day LIVE Marathon at 7pm (40 Marks in 5 Hours) - https://www.youtube.com/live/Xsd1…»
I'm proud of everyone who is studying despite tough AFM paper 🙏
Completed Professional Ethics in 3.5 Hours Effectively ❤️
Next SQC 1 & SA 220 at 11.10pm 🙌
Showing the 12 most recent of 595 posts we hold for @ankushchirimar1. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
Posts edited after publishing
@ankushchirimar1 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
9 September 2026
Most recent edit
9 September 2026
Posts recorded as deleted after publishing
We recorded 1 post on @ankushchirimar1 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 September 2026
Most recent seen missing
7 September 2026
Median time before seen missing
12 hours
Seen missing in the last 30 days
0
Polls
The 6 most recent of 105 polls we hold for this entry, as Telegram rendered them when we read the post. A poll’s figures keep moving after that, so each one is dated.
Shares as published. No per-option vote count is published by Telegram, so none is shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 595 most recent posts we hold, published 29 July 2026 to 5 November 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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
Names
Channels on the register whose handles appear in this channel's posts.
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 1 September 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.
PRATIK JAGATI FR & AFM @pratikjagati · 56,484 Telegram ranks this channel #3 of 83 here — alongside 82 others — read 23 August 2026
Clear CA with Shubham Keswani @ClearCAWithSK · 119,448 Telegram ranks this channel #3 of 89 here — alongside 88 others — read 19 August 2026
CA Shankar Lakhwani @cashankarlakhwani · 32,272 Telegram ranks this channel #4 of 86 here — alongside 85 others — read 6 September 2026
AIR1CA Guidance & Notes - By Atul & Ajay @air1ca · 157,497 Telegram ranks this channel #7 of 93 here — alongside 92 others — read 19 August 2026
CA Aakash Kandoi - FRWITHAK @aakashkandoi_FR · 110,432 Telegram ranks this channel #8 of 90 here — alongside 89 others — read 19 August 2026
CA Riddhi Baghmar @fastidt · 25,743 Telegram ranks this channel #9 of 87 here — alongside 86 others — read 15 September 2026
CA Siddharth Agarwal Law-Audit @siddharthagarwalclassesofficial · 22,455 Telegram ranks this channel #10 of 57 here — alongside 56 others — read 20 September 2026
Akshansh Garg - CA Final IDT @akshanshgarg · 42,859 Telegram ranks this channel #10 of 75 here — alongside 74 others — read 30 August 2026
CA BHAVIK CHOKSHI - Final FR/AFM @bhavikFRSFM · 43,941 Telegram ranks this channel #13 of 87 here — alongside 86 others — read 29 August 2026
CA Rohit Chipper AIR 17 @carohitchipper · 44,297 Telegram ranks this channel #13 of 87 here — alongside 86 others — read 28 August 2026
CA Nitin Guru @canitinguru · 25,051 Telegram ranks this channel #19 of 71 here — alongside 70 others — read 15 September 2026
CA Inter Audit Notes By CA Kapil Goyal @CAKapilGoyalAuditNotes · 26,577 Telegram ranks this channel #27 of 85 here — alongside 84 others — read 11 September 2026
Bhanwar Borana (BB)- Direct Tax @BBSIRDT · 207,658 Telegram ranks this channel #31 of 90 here — alongside 89 others — read 19 August 2026
CA Final & CA Inter Audit | Auditguru | Mentorship | CA Ravi Taori @AuditGuru · 29,152 Telegram ranks this channel #34 of 86 here — alongside 85 others — read 8 September 2026
Clear CA Inter with Shubham Keswani @clearcainterwithsk · 66,350 Telegram ranks this channel #37 of 90 here — alongside 89 others — read 22 August 2026
CA Sanidhya Saraf @sanidhyasaraf · 26,498 Telegram ranks this channel #38 of 80 here — alongside 79 others — read 11 September 2026
CA Inter by CA. Jai Chawla 🎯 @CAJaiChawla · 48,879 Telegram ranks this channel #38 of 91 here — alongside 90 others — read 26 August 2026
ACT-Arjun Chhabra Tutorial @ACTArjunChhabraTutorial · 40,038 Telegram ranks this channel #41 of 76 here — alongside 75 others — read 31 August 2026
CA NAMIT ARORA (NAMIT ARORA CLASSES) @namitaroraclasses · 48,040 Telegram ranks this channel #42 of 80 here — alongside 79 others — read 27 August 2026
CA Sarthak Niraj Jain @sjfasteducation · 27,872 Telegram ranks this channel #50 of 86 here — alongside 85 others — read 12 September 2026
CA Yash Khandelwal-Direct Tax @yashkhandelwaldt · 46,650 Telegram ranks this channel #50 of 91 here — alongside 90 others — read 27 August 2026
CA FINAL AFM & SCPM BY CA SANKALP KANSTIYA @cafinalsankalpcosting · 56,835 Telegram ranks this channel #54 of 84 here — alongside 83 others — read 23 August 2026
CA Divyesh Vaghela @Divyesh_Vaghela · 38,459 Telegram ranks this channel #60 of 85 here — alongside 84 others — read 31 August 2026
CA Wallah Intermediate @CA_Wallah_Intermediate · 46,655 Telegram ranks this channel #70 of 83 here — alongside 82 others — read 27 August 2026
This channel appears in 27 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 6 November 2026 — this
entry's latest reading, not the date you are reading this.
“CA Final with Ankush Chirimar Classes ♥️” (@ankushchirimar1), 38,836 subscribers as measured 6 November 2026. Telegram Register, tgregister.com/channel/ankushchirimar1.
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.