Telegram RegisterThe public register of Telegram

Channel

Core Ai Agents / LLM

@CoreAgents

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

140subscribers

+0 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1003175730188
TypeChannel
Username@CoreAgents
Created6 October 2025measured — dated from the channel’s first post
First recorded8 August 2026
Last confirmed live8 August 2026
Measurements held2
On Telegramt.me/CoreAgents

Growth

1407 August 2026 — 140 subscribers8 August 2026 — 140 subscribers7 August 20268 August 2026
2 measurements spanning 2 days. 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 139–141 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
8 Aug 2026, 22:30140no change
7 Aug 2026, 06:48140first reading

Engagement

18 posts held, back to 6 October 2025the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
no view readings in window
Avg views / post
no view readings
Reaction rate
this channel exposes no reaction counts
Posts in window
1
of 18 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 24 July 2026
Posts held18 (6 October 202524 July 2026)
Views total
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Aug 2026, 22:30 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
8
Links
4

Lifetime counters from Telegram’s own channel header, read 8 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Reaction mix

7 reactions across 1 post, in 3 distinct kinds. The most used accounts for 42.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥342.9%
228.6%
🤯228.6%

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 2 of the 18 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 7reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 18 most recent posts we hold, published 6 October 2025 to 24 July 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

9 Jun 2026, 05:41 UTC103 viewsread 8 August 2026
Photo

Best models for your hardware this week. 8-12GB - https://huggingface.co/LiquidAI/LFM2.5-8B-A1B incredible model, so fast, so small 16-32GB - latest Google model, Gemma 12B: https://huggingface.co/google/gemma-4-12B really solid performance up neck and neck with a model 2x its size from a month ago. Jetbrains new model, best in class on livecode bench 32-96gb - Nex-N2-Mini GPT style postrain of Qwen-35B it see

3 May 2026, 07:39 UTC106 viewsread 8 August 2026
Photo

Weekly best models for your hardware: ~~ 8 to 16gb ~~ Granite models are amazing: [NEW] - https://huggingface.co/ibm-granite/granite-4.1-8b Gemma-E4B is a good general QA model - https://huggingface.co/google/gemma-4-E4B-it Qwen3.5-9B is the best at this level imo - https://huggingface.co/Qwen/Qwen3.5-9B ~~ 16 to 64gb ~~ Another larger Granite: This is a general chat model, really dense with world knowledge. [

2 Apr 2026, 10:21 UTC114 viewsread 8 August 2026
Photo

Here are all the open weight models that can get close frontier level code, and tie for agentic purposes. GLM-5.* MiniMax-M2.* Kimi-K2.5 Deepseek-V3.2 Qwen-3.5-Plus-397B If you want AI at home for coding agents similar to Claude/Codex the VRAM needed 192GB for Q4 quant + REAP

31 Mar 2026, 00:16 UTC138 viewsread 8 August 2026
Photo

Give your ai agent eyes to see the entire internet for free Read & search - Twitter, - Reddit, - YouTube, - GitHub, - Bilibili, - XiaoHongShu One CLI, zero API fees. 📱 - https://www.opensourceprojects.dev/post/98258f76-86c9-4980-9616-b5ad00cb6df4 @CoreAti - @CorePrompts - @CoreUtil #free #Aiagent #tool

29 Mar 2026, 03:56 UTC148 viewsread 8 August 2026
Photo

—— 256 GB —— #1 MiniMax-M2.5 (M2.7) - 6bit MLX #2 Qwen3.5-262B-REAP (4-6 bits) #3 Nemotron-122B (8-9bits) #4 GLM-5-358B (4bit) —— 512 GB —— #1 MiniMax-M2.* - FP16 #2 Qwen3.5-397B - 8bit #3 Kimi-k2.5-530B-PRISM - 4bit #4 GLM-5 - 4bit

29 Mar 2026, 03:27 UTC149 viewsread 8 August 2026
Photo

Best models to run on your hardware: —— 64 GB —— - Qwen3-coder-next-80B-4bit (coding, Claude code, general agent) - Qwen3.5-122B-reap: (browser use, multimodal, tool calling, general agent) —— 96 GB —— - GLM-4.6V (multimodal and tool calls) - Hermes-70B (Jailbroken) - Nemotron-120B-Super: (openclaw) - Mistral-4-Small (general agent) —— 192 GB —— All these are excellent top tier LLMs and approach sonnet in capab

29 Mar 2026, 03:23 UTC139 viewsread 8 August 2026
Photo

Best models to run on your hardware level: ---- 8 GB ---- Autocomplete for coding (like Cursor Tab) - https://huggingface.co/NexVeridian/zeta-2-4bit - https://huggingface.co/bartowski/zed-industries_zeta-2-GGUF Tool calling, assistant style - https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-4B-GGUF ---- 16 Gb ---- Here things get better: Multimodal - huggingface.co/Qwen/Qwen3.5-9B - https://huggingface.co/

11 Mar 2026, 09:23 UTC131 views0 reactionsread 8 August 2026

📂 SaaS ┃ ┣ 📂 Idea ┃ ┣ 📂 Problem Discovery ┃ ┣ 📂 Market Research ┃ ┣ 📂 Niche Selection ┃ ┣ 📂 Competitor Analysis ┃ ┗ 📂 Opportunity Mapping ┃ ┣ 📂 Validation ┃ ┣ 📂 Customer Interviews ┃ ┣ 📂 Landing Page Test ┃ ┣ 📂 Waitlist ┃ ┣ 📂 Pre Sales ┃ ┗ 📂 Demand Testing ┃ ┣ 📂 Planning ┃ ┣ 📂 Product Roadmap ┃ ┣ 📂 Feature Prioritization ┃ ┣ 📂 MVP Scope ┃ ┣ 📂 Tech Stack ┃ ┗ 📂 Development Plan ┃ ┣ 📂 Design ┃ ┣ 📂 Wireframes ┃ ┣ 📂 UI De

26 Feb 2026, 16:10 UTC128 views7 reactionsread 8 August 2026

you can outsource your thinking but you cannot outsource your understanding

🔥32🤯2

25 Feb 2026, 20:59 UTC129 viewsread 8 August 2026
Photo

send this prompt to your OpenClaw to steal ANY writing style from books, articles, tweets, emails...

Showing the 12 most recent of 18 posts we hold for @CoreAgents. 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 8 August 2026 — this entry's latest reading, not the date you are reading this.

“Core Ai Agents / LLM” (@CoreAgents), 140 subscribers as measured 8 August 2026. Telegram Register, tgregister.com/channel/CoreAgents.

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.