Telegram RegisterThe public register of Telegram
Telegram profile photo for ✧Hehestl | *hysterical hehe*

Channel

✧Hehestl | *hysterical hehe*

@hehestl

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

30,652subscribers

-77 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001740544097
TypeChannel
Username@hehestl
Descriptionwhich means hehe? making stl search friendly *Your worst nightmare* Support: @PhiloraBot ADS: https://adsly.me/@hehestl https://boosty.to/hehestl
CreatedBetween 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live5 September 2026
Measurements held26
Confirmed unchanged1 time, most recently 5 September 2026
On Telegramt.me/hehestl

Growth

30,65230,73030,6917 August 2026 — 30,729 subscribers7 August 2026 — 30,729 subscribers8 August 2026 — 30,730 subscribers9 August 2026 — 30,718 subscribers10 August 2026 — 30,716 subscribers13 August 2026 — 30,717 subscribers14 August 2026 — 30,716 subscribers16 August 2026 — 30,717 subscribers17 August 2026 — 30,708 subscribers18 August 2026 — 30,701 subscribers19 August 2026 — 30,709 subscribers20 August 2026 — 30,704 subscribers21 August 2026 — 30,712 subscribers22 August 2026 — 30,716 subscribers24 August 2026 — 30,710 subscribers25 August 2026 — 30,697 subscribers26 August 2026 — 30,690 subscribers27 August 2026 — 30,691 subscribers28 August 2026 — 30,683 subscribers29 August 2026 — 30,674 subscribers30 August 2026 — 30,676 subscribers31 August 2026 — 30,672 subscribers1 September 2026 — 30,671 subscribers2 September 2026 — 30,661 subscribers3 September 2026 — 30,659 subscribers5 September 2026 — 30,652 subscribers7 August 20265 September 2026
26 measurements spanning 29 days, net -77. 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 30,640–30,742 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 26
Measured (UTC)SubscribersChange
5 Sept 2026, 05:5730,652-7
3 Sept 2026, 09:3430,659-2
2 Sept 2026, 05:1330,661-10
1 Sept 2026, 04:3730,671-1
31 Aug 2026, 07:1330,672-4
30 Aug 2026, 09:0630,676+2
29 Aug 2026, 11:2530,674-9
28 Aug 2026, 13:4330,683-8
27 Aug 2026, 16:2430,691+1
26 Aug 2026, 16:3430,690-7
25 Aug 2026, 15:4330,697-13
24 Aug 2026, 14:0930,710-6
22 Aug 2026, 22:5930,716+4
21 Aug 2026, 16:0730,712+8
20 Aug 2026, 14:4330,704-5
19 Aug 2026, 13:5430,709+8
18 Aug 2026, 13:1330,701-7
17 Aug 2026, 13:4730,708-9
16 Aug 2026, 08:4430,717+1
14 Aug 2026, 21:5330,716first reading

Engagement

230 posts held, back to 3 August 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 70 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
2.68%
avg views ÷ 30,652 subscribers
Avg views / post
820
205 posts measured
Reaction rate
0.199%
reactions ÷ views · ER floor
Posts in window
205
of 230 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 45 of 205 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 6 September 2026
Posts held230 (3 August 20266 September 2026)
Views total168,190
Reactions total74
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken6 Sept 2026, 23:03 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
39,600
Videos
362
Links
6,780

Lifetime counters from Telegram’s own channel header, read 6 September 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
35s
Average length
12s

Measured directly from 3 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

80 reactions across 48 posts, in 4 distinct kinds. The most used accounts for 50.0% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
custom 52422983411690508154050.0%
custom 52378299559785473222328.7%
custom 5395383890565149433911.3%
custom 5395833560756140921810.0%

Custom emoji. Every row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them are Telegram’s.

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 49 of the 230 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 80 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 230 most recent posts we hold, published 3 August 2026 to 6 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.

Recent posts

6 Sept 2026, 19:50 UTC266 viewsread 6 September 2026

it's just that our experience of working with models and 1000 authors of these very models (in the neural network sample, it most often analyzes fdm authors as well, but in general we don't even discuss fdm authors

6 Sept 2026, 19:47 UTC274 viewsread 6 September 2026

Thesis → calibrated figure 85% of models are trash → raw feed 70%; known names 40%; top tier 20% 50% of authors don’t know what they’re making or who for → 45% 90% have no system / technical process → 80% ~60% test what they sculpted → slicer check ~60%; print-before-release ~25% Renders lie about the model — 50% → 60% 90% still don’t get normals / real geometry → in practice 75% 10% of selected authors ship >25M pol

6 Sept 2026, 19:46 UTC263 viewsread 6 September 2026

We didn’t ask the neural network to find information for us, and now, having fed “our feelings” into the neural network, let’s compare our experience.

6 Sept 2026, 19:43 UTC290 viewsread 6 September 2026

Approximately 25% of authors stop working on 3D modeling within the first year.

6 Sept 2026, 19:41 UTC292 viewsread 6 September 2026

10% of the selected authors are so stupid that their models contain more than 25 million polygons, and the model is just a complete waste.

6 Sept 2026, 19:41 UTC289 viewsread 6 September 2026

90% of authors still don’t understand what normals and intrinsic geometry are.

6 Sept 2026, 19:39 UTC291 viewsread 6 September 2026

The render is lying about what the model actually is — 50 %.

6 Sept 2026, 19:39 UTC290 viewsread 6 September 2026

Testing what they’ve modeled and what they’ve sculpted, or having, well, let’s say 60% of the authors.

6 Sept 2026, 19:38 UTC297 viewsread 6 September 2026

90% of authors and “studios” do not have a system or technical processes in place.

6 Sept 2026, 19:38 UTC299 viewsread 6 September 2026

50% of authors don’t understand at all what they’re doing and who they’re doing it for.

6 Sept 2026, 19:37 UTC295 viewsread 6 September 2026

In 2026, as we dive deeper and deeper into this rabbit hole, we can adjust this same phrase: the take is that 85% of the models are really just trash.

Showing the 12 most recent of 230 posts we hold for @hehestl. 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

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

Named by 2 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.

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.

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

“✧Hehestl | *hysterical hehe*” (@hehestl), 30,652 subscribers as measured 5 September 2026. Telegram Register, tgregister.com/channel/hehestl.

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.