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Channel

猫猫的朋友圈

@moohrburrow

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

34subscribers

+1 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-1002061764234
TypeChannel
Username@moohrburrow
CreatedBetween 1 November 2023 and 31 May 2024 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded11 August 2026
Last confirmed live2 October 2026
Measurements held3
Confirmed unchanged1 time, most recently 2 October 2026
On Telegramt.me/moohrburrow

Topic

Technology — 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 2 October 2026 and assigned it the closest of 31 fixed categories, at 99% 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

333433.57 August 2026 — 33 subscribers11 August 2026 — 33 subscribers2 October 2026 — 34 subscribers7 August 20262 October 2026
3 measurements spanning 56 days, net +1. 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 33–34 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
2 Oct 2026, 17:5734+1
11 Aug 2026, 01:3033no change
7 Aug 2026, 15:2733first reading

Engagement

16 posts held, back to 5 April 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 16 posts for this entry, the most recent from 31 July 2026. An engagement rate over an empty window would be a number about nothing.

Reaction mix

26 reactions across 9 posts, in 7 distinct kinds. The most used accounts for 26.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
😁726.9%
🥰519.2%
👍415.4%
❤311.5%
😭311.5%
🤬311.5%
😨13.85%

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 9 of the 16 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 26 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 16 most recent posts we hold, published 5 April 2026 to 31 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

22 Jul 2026, 07:16 UTC54 views2 reactionsread 11 August 2026

体验了一下 Gemini 3.6 Flash,我觉得你别碰瓷K3 GLM5.2了,这玩意智商有没有Qwen3.6 27b高都难说,最难用的模型,没有之一🤣 350TPS输出250的垃圾token p.s. 作为爱吃狗屎模型的人,我说真的,豆包新模型的code能力真的吊打这模型,豆包至少能让你感觉用的是一个大模型,这玩意让你怀疑有人用世界上最好的集群跑的8b的千问

😁2

12 Jul 2026, 11:21 UTC85 views2 reactionsread 11 August 2026

如果您的WSL git push 在SSH Key那里卡很久,可以快速三次git push +ctrl c,然后再git push就会成功(我也不知道为啥)

😁2

25 Jun 2026, 08:15 UTC123 views2 reactionsread 11 August 2026
Photo

ping0笑话之 《surfshark》 《家宽IP》 《纯净》 《1-10》 《极好》

😁2

23 Jun 2026, 11:20 UTC112 views1 reactionsread 11 August 2026
Photo

坏了,现在说gemini是美国豆包还真是侮辱豆包了

😁1

3 Jun 2026, 01:14 UTC96 views3 reactionsread 11 August 2026

void setup() { // put your setup code here, to run once: pinMode(4, OUTPUT); pinMode(5, INPUT); Serial.begin(9600); } // Octave 5 #define NOTE_C5 523 // Do #define NOTE_D5 587 // Re #define NOTE_E5 659 // Mi #define NOTE_F5 698 // Fa #define NOTE_G5 784 // Sol #define NOTE_A5 880 // La #define NOTE_B5 988 // Si // Octave 6, one octave higher #define NOTE_C6 1047 // Do #define NOTE_D6 1175 //…

❤3

31 May 2026, 13:11 UTC73 views7 reactionsread 11 August 2026
Photo

最近发现超市的五花肉价格非常不错,于是尝试做了一下台式卤肉饭 配料表: 五花肉 两斤 红葱 一个 生抽 老抽 冰糖 或 白砂糖(我用的白砂糖,没买到冰糖) 八角 香叶 桂皮 油 料酒 具体步骤: 1. 准备冷水,放入适量料酒,冷水下五花肉,待沸腾后小火煮20分钟 2. 期间,准备红葱头或洋葱,切丁后下油锅,炸至金黄,沥干油后盛出备用,葱油可拌面等 3. 取出五花肉,冲洗掉肉表面的浮沫,切成8mm细条。过滤汤中浮沫。 4. 取少许葱油,下五花肉,炸至金黄后,加入适量红葱酥、糖、少许生抽,待糖融化后再加入适量生抽调味,老抽调色 5. 加入三篇香叶、两颗八角、少许桂皮,倒入汤中。熬煮3小时以上,越久越好

👍4🤬3

15 May 2026, 17:38 UTC130 viewsread 11 August 2026
Photo

最近一直在研究能不能用8GB的VRAM跑出来什么有价值的东西。答案是,有的! 电脑配置: r7 7745hx + 4070 Laptop GPU (8GB VRAM), 64GB DDR5 5600Mhz RAM (实际上32G足矣,因为运行的Q4) llama.cpp的效率远比我想象中的要好很多,搭配turboquant,APEX,编码速度高达1000TPS,解码速度30TPS左右,并且基础功能搭配opencode已经可以实现部分非常简单的工程 用到的模型: https://huggingface.co/mudler/Qwen3.6-35B-A3B-uncensored-heretic-APEX-GGUF 由于llama.cpp 暂无原生turboquant支持,所以使用的这个分支: https://github.com/atomicmilkshake/llama-cpp-turboquant .\llama-ser…

24 Apr 2026, 03:26 UTC170 viewsread 11 August 2026
Photo

flash/pro 速度为官方API实测,测试时间11:20AM UTC+8

Showing the 12 most recent of 16 posts we hold for @moohrburrow. 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.

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 2 October 2026 — this entry's latest reading, not the date you are reading this.

“猫猫的朋友圈” (@moohrburrow), 34 subscribers as measured 2 October 2026. Telegram Register, tgregister.com/channel/moohrburrow.

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.