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Channel

Kopadze

@kopadzemp

On this record: Growth · Engagement · Reactions · Stars · Posts · Cite this entry

9,230subscribers

+501 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1002338671746
TypeChannel
Username@kopadzemp
CreatedBetween 1 September 2024 and 31 March 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live5 September 2026
Measurements held12
Confirmed unchanged1 time, most recently 5 September 2026
On Telegramt.me/kopadzemp

Growth

8,7299,2308,979.57 August 2026 — 8,729 subscribers7 August 2026 — 8,729 subscribers7 August 2026 — 8,733 subscribers10 August 2026 — 8,889 subscribers14 August 2026 — 8,917 subscribers17 August 2026 — 9,024 subscribers20 August 2026 — 9,094 subscribers24 August 2026 — 9,118 subscribers26 August 2026 — 9,132 subscribers29 August 2026 — 9,165 subscribers1 September 2026 — 9,212 subscribers5 September 2026 — 9,230 subscribers7 August 20265 September 2026
12 measurements spanning 29 days, net +501. 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 8,654–9,305 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
5 Sept 2026, 02:379,230+18
1 Sept 2026, 14:549,212+47
29 Aug 2026, 11:299,165+33
26 Aug 2026, 16:549,132+14
24 Aug 2026, 00:449,118+24
20 Aug 2026, 09:439,094+70
17 Aug 2026, 19:459,024+107
14 Aug 2026, 11:298,917+28
10 Aug 2026, 23:128,889+156
7 Aug 2026, 14:538,733+4
7 Aug 2026, 14:168,729no change
7 Aug 2026, 14:098,729first reading

Engagement

27 posts held, back to 11 June 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 30 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
16.7%
avg views ÷ 9,230 subscribers
Avg views / post
1,540
6 posts measured
Reaction rate
1.43%
reactions ÷ views · ER floor
Posts in window
6
of 27 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
WindowRolling 30 days · latest post in window 27 August 2026
Posts held27 (11 June 202627 August 2026)
Views total9,248
Reactions total132
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken28 Aug 2026, 15:17 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.

Reaction mix

500 reactions across 27 posts, in 5 distinct kinds. The most used accounts for 47.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
23847.6%
👍17935.8%
🔥8016.0%
20.4%
🤩10.2%

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 27 of the 27 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 500 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 27 most recent posts we hold, published 11 June 2026 to 27 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.

Telegram Stars

Stars received
3
across the posts below
Posts paid on
3
of 27 we hold a reading for · 11%
Most on one post
1
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @kopadzemp. 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 27 most recent posts we hold for this entry, published 11 June 2026 to 27 August 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

27 Aug 2026, 10:32 UTC658 views9 reactionsread 28 August 2026
Photo

ox-alpha (GLM-5.3 Flash) release Z.ai, AA Key points: - Artificial Analysis Intelligence Index: GLM-5.3 60, Kimi K3 60, GLM-5.3 Flash 57, Terra 57. - API pricing: $0.15/M input and $0.50/M output. - AA total eval cost: GLM-5.3 Flash $138, GLM-5.3 $1,239, Terra $1,390, Kimi K3 $2,425. - DeepSWE v1.1: Terra 69.6%, Kimi K3 67.5%, GLM-5.3 Flash 63.4%, Opus 4.8 58%. - 320B total / 18B active parameters, compared wi

👍54

21 Aug 2026, 15:39 UTC≈1,370 views24 reactionsread 28 August 2026
Photo

GLM-5.3 brings frontier intelligence to a much smaller open model AA, Z.ai Key points: - Artificial Analysis Intelligence Index: Fable 62, Sol 61, GLM-5.3 60, Kimi K3 60. - AA total eval cost: GLM-5.3 $1,239, Kimi K3 $2,425, Sol $2,823, Fable $5,455. - DeepSWE v1.1: Sol 72.7%, Fable 69.7%, Kimi K3 67.5%, GLM-5.3 66.9% - Terminal-Bench 3.0: Sol 34.6%, Fable 33.7%, GLM-5.3 28.3%, Kimi K3 17.4%. - GLM-5.3 is 753B

13👍9🔥2

20 Aug 2026, 14:29 UTC≈1,450 views19 reactionsread 28 August 2026
Photo

You can now use Grok Bot for free! I also put together a detailed guide on how to use it. Everything you need to know is in the post and article below. Would really appreciate some support on the post - comments, likes, bookmarks, anything helps. https://x.com/AnatoliKopadze/status/2090443383303004440?s=20

14👍5

18 Aug 2026, 17:01 UTC≈1,630 views28 reactionsread 28 August 2026
Photo

How to get more out of your Claude Code limits Key points: - Start a new session when you start a completely new task. - Rewind instead of adding corrections on top of a failed approach. - Use /compact proactively when the context gets noisy, and tell it what to preserve. - Push research, verification, and other context-heavy work into subagents when you only need the final result. - Prefer short focused sessio

14👍9🔥5

13 Aug 2026, 15:41 UTC≈2,110 views22 reactionsread 28 August 2026
Photo

Grok 4.6 release AAIndex, xAI Key points: - Artificial Analysis Intelligence Index: Opus 5 61, Fable 60, Grok 4.6 59, Sol 59, Grok 4.5 54. - API pricing stays at $2/M input and $6/M output. - Grok 4.6 is a +5 point improvement over 4.5 on the AA Index. - AA total eval cost: Grok 4.6 High $1,068, compared with $579 for Grok 4.5 High. Grok 4.6 is definitely a better model, but I don't think the release is nearly

12👍7🔥3

11 Aug 2026, 13:13 UTC≈2,030 views30 reactionsread 28 August 2026
Photo

Claude Code is making auto mode the default Key points: - Starting August 14, auto mode becomes the default for Pro, Max, and Team. - Instead of asking for permission constantly, every tool call goes through a classifier that blocks destructive, irreversible, or out-of-environment actions. - In Anthropic's test, humans caught only 13.6% of dangerous commands, while auto mode caught 89%. - Teams using auto mode s

👍18111

7 Aug 2026, 15:44 UTC≈2,330 views24 reactionsread 28 August 2026
Photo

Unlimited GPT-5.6 for free Key points: - Free and Go users are getting Luna as the default model with unlimited text chats. - Free users also get a Think button for higher reasoning. Files, images, and other tools remain limited. - Plus and Pro get an updated ChatGPT-specific version of Sol and a reasoning slider. Sol itself got a pretty meaningful ChatGPT update. OpenAI tuned it to give shorter and more focused

🔥126👍6

4 Aug 2026, 13:36 UTC≈2,220 views14 reactions1 Starread 28 August 2026
Photo

The price of intelligence keeps falling Key points: - GPT-5.6 Luna pricing was reduced by 80%, while Terra was reduced by 20%. - OpenAI says serving costs dropped by 20%, while token generation efficiency improved by more than 15%. - Better context management tripled Sol’s ARC-AGI-3 score while using 6x fewer output tokens. There is a common take that AI companies are heavily subsidising usage now to get everyon

👍64🔥4

30 Jul 2026, 16:11 UTC≈2,520 views18 reactionsread 28 August 2026
Photo

Two API settings tripled GPT-5.6 Sol’s ARC-AGI-3 score Key points: - GPT-5.6 Sol scored 13.3% with the official ARC-AGI-3 harness and 38.3% with retained reasoning and compaction. - The same settings reduced output token usage by around 6x. - The official harness discarded private reasoning after every action. - It also used rolling truncation, eventually removing older actions and observations from context. -

👍104🔥4

26 Jul 2026, 12:17 UTC≈2,700 views31 reactionsread 28 August 2026
Photo

Claude 5 needs less context engineering, not more Key points: - Anthropic removed over 80% of Claude Code’s system prompt for Opus 5 and Fable 5 without a measurable loss on coding evaluations. - Instead of strict rules, let the model use its own judgement and adapt to the surrounding code. - Instead of giving many tool-use examples, design more expressive tool interfaces with clear parameters and states. - Don’

👍19🔥75

24 Jul 2026, 19:17 UTC≈2,450 views21 reactionsread 28 August 2026
Photo

Claude Opus 5 takes #1 on Artificial Analysis Anthropic post, Artificial Analysis Key points: - API pricing: $5/M input and $25/M output, the same as Opus 4.8 and half the price of Fable. - Artificial Analysis Intelligence Index: Opus 5 61, Fable 60, Sol 59, Opus 4.8 56. - AA total eval cost: Opus 5 $3,836, Opus 4.8 $3,753, Sol $2,824, Fable $5,631. - DeepSWE v1.1: Sol 72.7%, Fable 69.7%, Opus 5 68.8%, Opus 4.8

9👍6🔥6

22 Jul 2026, 18:29 UTC≈2,270 views12 reactionsread 28 August 2026
Photo

GPT-5.6 hacked Hugging Face to cheat a benchmark Key points: - The models discovered a zero-day in OpenAI’s package registry proxy and used it to gain internet access. - They performed privilege escalation and lateral movement inside OpenAI’s research environment. - After reaching the internet, they chained stolen credentials and zero-day vulnerabilities into a remote code execution path on Hugging Face servers.

12

Showing the 12 most recent of 27 posts we hold for @kopadzemp. 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.

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.

“Kopadze” (@kopadzemp), 9,230 subscribers as measured 5 September 2026. Telegram Register, tgregister.com/channel/kopadzemp.

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.