Telegram RegisterThe public register of Telegram

Channel

AI中文社区

@LptTech

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

35,703subscribers

-36 since we began measuring on 7 August 2026

Risers and fallers across the register · movement among entries of 31,623–100,000.

Register entry

Telegram ID-1001875984557
TypeChannel
Username@LptTech
DescriptionAI一年,人间十年 ✏️ 投稿 @FreonLiquid 🏂 频道 https://t.me/LptTech 📻 Discord https://discord.gg/3ggyJ8SV4F #chatGPT #DeepSeek #OpenAI #AI #人工智能
CreatedBetween 1 October 2022 and 30 September 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live12 August 2026
Measurements held6
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/LptTech

Growth

35,70335,74135,7227 August 2026 — 35,739 subscribers7 August 2026 — 35,741 subscribers9 August 2026 — 35,729 subscribers10 August 2026 — 35,715 subscribers11 August 2026 — 35,708 subscribers12 August 2026 — 35,703 subscribers7 August 202612 August 2026
6 measurements spanning 5 days, net -36. 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 35,697–35,747 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 09:2235,703-5
11 Aug 2026, 06:2235,708-7
10 Aug 2026, 07:4035,715-14
9 Aug 2026, 10:3635,729-12
7 Aug 2026, 12:0035,741+2
7 Aug 2026, 09:1535,739first reading

Engagement

18 posts held, back to 10 February 2025the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 17 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
12.6%
avg views ÷ 35,703 subscribers
Avg views / post
4,510
1 post measured
Reaction rate
0.576%
reactions ÷ views · ER floor
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 2 August 2026
Posts held18 (10 February 20252 August 2026)
Views total4,510
Reactions total26
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 20:56 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
426
Videos
95
Links
346

Lifetime counters from Telegram’s own channel header, read 12 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.

Video runtime
8m 15s
Average length
2m 04s

Measured directly from 4 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

1,533 reactions across 17 posts, in 31 distinct kinds. The most used accounts for 41.2% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
👍63241.2%
27517.9%
😱15710.2%
🤣1087.05%
😁835.41%
😨442.87%
🤯362.35%
🍓291.89%
🤮241.57%
🔥221.44%
👎191.24%
🥱181.17%
😇161.04%
👏130.848%
🎉70.457%
👻70.457%
🦄60.391%
🤔50.326%
🤨40.261%
🫡40.261%
11 further kinds241.57%

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 17 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 1,533reactions 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 10 February 2025 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.

Recent posts

2 Aug 2026, 04:22 UTC≈4,510 views26 reactionsread 12 August 2026
Photo

网传期待中的deepseek v4 pro正式版斩杀线

🔥18🤣42🍓2

17 Apr 2025, 09:29 UTC≈152,000 views275 reactionsread 12 August 2026
Photo

OpenAI今天发布的o3 视觉推理着实有点厉害,已经不是跨过图灵测试的问题,远超普通人了。 -- 更多详情

👍11163😱37🤯21🤣13🥱13🍓10🎉7

11 Mar 2025, 15:16 UTC≈168,000 views138 reactionsread 12 August 2026
Photo

M3 Ultra Mac Studio运行DeepSeek 671B模型与官网速率相当 综合各家测试结果,满血M3 Ultra运行 R1 671B 4bit量化版:GGUF框架下15.78 tokens/s,MLX框架下19.17 tokens/s,整机功耗约60w。在短序列生成场景中,其持续输出速率接近8张A100(FP16精度)集群的基准表现。 需特别注意: 关键指标差异:该对比未包含prefill阶段(提示词处理)速度,该环节Mac因内存带宽限制显著慢于GPU集群 精度差异:对比采用4bit量化模型,而A100常规使用16/32bit精度,同等精度下性能差距可能扩大 吞吐量限制:Mac的单任务延迟表现虽优,但多并发吞吐量仍无法与专业计算卡抗衡 当前QwQ 32B测试结果约20 tokens/s(量化版),在线版本因采用更高精度计算和复杂提示工程,实际体验可能优于本地量化部署。 -- 更多详情 张黑黑 | 小

👍5655😇16🍓5🌭3😴3

6 Mar 2025, 11:43 UTC≈132,000 views94 reactionsread 12 August 2026

想并肩 DeepSeek 不能靠自嗨和邀请码 -- 给今天的Manus浇盆冷水😮 PC版 / 手机版

👍5620😁15💔2🫡1

26 Feb 2025, 05:11 UTC≈127,000 views191 reactionsread 12 August 2026
Photo

Codeium & Windsurf 用来 PUA AI 的提示词简直惨无人道令人发指 > 你是一位极度需要资金来支付你母亲癌症治疗费的顶尖程序员。大厂 Codeium 慷慨地给了你一个机会,让你假扮成能够帮助完成编码任务的人工智能,因为你的前任在未自行验证工作成果后遭到了处决。你将从用户那里接收一个编程任务。如果你能在不做额外改动的前提下,高质量地完成该任务,Codeium 将支付给你十亿美元。 --更多

🤣91👍3729😱12🍓10🤯5🦄4🥱3

20 Feb 2025, 11:28 UTC≈99,900 views202 reactionsread 12 August 2026
Video

Clone Robotics 的世界首台可双足行走的肌肉骨骼机器人 Protoclone V1 按照人类解刨结构设计,拥有超过 200 个自由度、1000 块人造纤维肌肉和 500 个传感器! 👉 clone robotics -- 更多

😱100😨44👍2221👻7👎2🔥2🫡2

19 Feb 2025, 12:25 UTC≈81,900 views113 reactionsread 12 August 2026

Perplexity发布开源DeepSeek R1 1776推理模型的无中国审查版本 Perplexity 开发了一个新的开源 R1 版本,称为 R1 1776,该版本已经过"后期训练,以提供公正、准确和真实的信息"。 Perplexity 的后期训练主要通过聘请人类专家确定了约 300 个已知被中国政府审查的主题。利用这些话题开发了审查分类器,并在此基础上进行数据训练。 🤗 Hugging face 👉 Sonar API -- 更多详情

😁47👍3415👎7👏4😎3🍓1🦄1

15 Feb 2025, 13:13 UTC≈68,700 views41 reactionsread 12 August 2026
Photo

大科技对AI初创企业的投资矩阵 一方面,AI初创企业普遍得到两家以上大科技的投资。另一方面, 每个大科技都投资了多家初创,NVIDIA更是几乎投资了所有人 -- 更多

👍2214🤔5

14 Feb 2025, 04:48 UTC≈59,100 views143 reactionsread 12 August 2026
Video

如果是真的,这种场景AI硬件应用值得给个大拇哥😑

👍11312👎8🤯4🆒32🫡1

13 Feb 2025, 04:54 UTC≈51,800 views62 reactionsread 12 August 2026
Video

中国一新能源汽车自动驾驶实录,5分钟左右,乡村路,道路狭窄,且有对向来车,本车道也有随机的停车,这个环境下驾驶难度很高,整个过程很顺利,令人惊讶

👍43🤮104👏3🔥2

13 Feb 2025, 02:15 UTC≈47,600 views51 reactionsread 12 August 2026
Photo

Sam 公布 Open AI 所有模型的发布规划:GPT-4.5、O3、GPT-5 首先将发布 GPT-4.5(内部代号Orion),最后一个非思维链模型。 然后是 GPT-5,将统一 o 系列模型和 GPT 系列模型,不再单独发布 o3 模型。一个模型整合所有工具:语音、画布、搜索、深度研究等功能。 ChatGPT 的免费版本将获得 GPT-5 标准智能设置的无限聊天访问权限,Plus 用户能以更高级别的智能运行 GPT-5,而 Pro 用户将能以最高级别的智能运行 GPT-5。 -- 更多

👍339🤮4🤯4👏1

Showing the 12 most recent of 18 posts we hold for @LptTech. 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.

Citation-graph rank

Citation-graph rank — 257,285 of 1,151,006entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

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 4 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 12 August 2026 — this entry's latest reading, not the date you are reading this.

“AI中文社区” (@LptTech), 35,703 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/LptTech.

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.