Giveaways & airdrops — 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 20 September 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 why it has no browse page of its own yet.
Growth
8 measurements spanning 42 days, net -10. 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 743–758 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
18 Sept 2026, 07:38
746
+1
9 Sept 2026, 21:56
745
-2
30 Aug 2026, 23:25
747
-2
24 Aug 2026, 13:43
749
-2
16 Aug 2026, 06:56
751
-3
8 Aug 2026, 02:00
754
no change
7 Aug 2026, 19:34
754
-2
7 Aug 2026, 18:19
756
first reading
Engagement
9 posts held, back to 9 January 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 1 page 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 9 posts for this entry, the most recent from 2 August 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
178 reactions across 7 posts, in 11 distinct kinds. The most used accounts for 42.7% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
76
42.7%
🤣
46
25.8%
👍
18
10.1%
😁
12
6.74%
👀
9
5.06%
🔥
7
3.93%
👎
3
1.69%
🙊
3
1.69%
👏
2
1.12%
✍
1
0.562%
🍌
1
0.562%
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 7 of the 9 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 178 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 9 most recent posts we hold, published 9 January 2026 to 2 August 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.
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X Post
Join the @PointsOTC channel if you haven’t done so.
This channel will not be used by POTC anymore, we will migrate all activity to @PointsOTC. @PointsOTC gives you the opportunity to discuss any Variational and Extended related issue. New updates regarding points trading will be shared in @PointsOTC as of now.
@PointsOTC
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X post
VariationalOTC by POTC pinned «🚨 - How It Works (VariationalOTC) 1. Collateral Setup - No one sends collateral until a trade is matched by a buyer or seller through the @POTCtradebot. - Once given the green light by VariationalOTC, both the buyer and seller deposit collateral into the…»
🚨 - How It Works (VariationalOTC)
1. Collateral Setup
- No one sends collateral until a trade is matched by a buyer or seller through the @POTCtradebot.
- Once given the green light by VariationalOTC, both the buyer and seller deposit collateral into the Multi Sig - this locks in the trade.
2. Workflow
- Use the @POTCtradebot to create an order by using the /start command. Select Extended, fill in the price, amo…
Showing the 9 most recent of 9 posts we hold for @OTCVariational. 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.
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.
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 18 September 2026 — this
entry's latest reading, not the date you are reading this.
“VariationalOTC by POTC” (@OTCVariational), 746 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/OTCVariational.
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.