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Channel

Ai一线 | 软件 资讯 新闻

@FollowBun

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

22,504subscribers

+3,507 since we began measuring on 19 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1002739887158
TypeChannel
Username@FollowBun
CreatedBetween 1 June 2025 and 30 September 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded19 August 2026
Last confirmed live4 September 2026
Measurements held15
Confirmed unchanged1 time, most recently 4 September 2026
On Telegramt.me/FollowBun

Growth

18,99722,50420,750.519 August 2026 — 18,997 subscribers20 August 2026 — 19,147 subscribers21 August 2026 — 19,492 subscribers22 August 2026 — 19,954 subscribers24 August 2026 — 20,311 subscribers25 August 2026 — 20,514 subscribers26 August 2026 — 20,757 subscribers27 August 2026 — 20,962 subscribers28 August 2026 — 21,133 subscribers29 August 2026 — 21,313 subscribers30 August 2026 — 21,414 subscribers31 August 2026 — 21,778 subscribers1 September 2026 — 21,980 subscribers3 September 2026 — 22,233 subscribers4 September 2026 — 22,504 subscribers19 August 20264 September 2026
15 measurements spanning 16 days, net +3,507. 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 18,471–23,030 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
4 Sept 2026, 10:2022,504+271
3 Sept 2026, 01:5522,233+253
1 Sept 2026, 20:2721,980+202
31 Aug 2026, 20:5921,778+364
30 Aug 2026, 19:3421,414+101
29 Aug 2026, 21:0821,313+180
28 Aug 2026, 22:3421,133+171
27 Aug 2026, 19:0520,962+205
26 Aug 2026, 18:3320,757+243
25 Aug 2026, 15:4220,514+203
24 Aug 2026, 14:0220,311+357
22 Aug 2026, 18:3819,954+462
21 Aug 2026, 06:3719,492+345
20 Aug 2026, 05:0619,147+150
19 Aug 2026, 12:1518,997first reading

Engagement

23 posts held, back to 5 August 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
11.9%
avg views ÷ 22,504 subscribers
Avg views / post
2,680
12 posts measured
Reaction rate
0.432%
reactions ÷ views · ER floor
Posts in window
12
of 23 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 29 August 2026
Posts held23 (5 August 202629 August 2026)
Views total32,157
Reactions total139
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken3 Sept 2026, 12:22 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

263 reactions across 22 posts, in 4 distinct kinds. The most used accounts for 89.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
23689.7%
👍249.13%
🥰20.76%
🍓10.38%

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 22 of the 23 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 263 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 23 most recent posts we hold, published 5 August 2026 to 29 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

29 Aug 2026, 21:31 UTC774 views11 reactionsread 3 September 2026

🚨 Codex 额度现已提前重置! 重置时间:2026-08-30 05:28:14(北京时间) #Codex #Credits ──────────── 🚨 Codex quota has now been reset early! Reset time: 2026-08-29 21:28:14 UTC #Codex #Credits

11

27 Aug 2026, 16:46 UTC≈1,160 views11 reactionsread 3 September 2026

🚨 Codex 额度现已提前重置! 重置时间:2026-08-28 00:30:09(北京时间) #Codex #Credits ──────────── 🚨 Codex quota has now been reset early! Reset time: 2026-08-28 16:30:09 UTC #Codex #Credits

11

23 Aug 2026, 06:50 UTC≈1,750 views12 reactionsread 3 September 2026

🎁 Codex 明日将再次全量重置额度! Tibo 确认,团队发现了部分导致 Codex 额度消耗偏快的问题,并将在明日推送修复。 作为此次修复的一部分,所有付费订阅用户的 Usage 将进行一次完整重置。 ⏰ 预计时间:北京时间 8 月 25 日凌晨 5 点左右

12

19 Aug 2026, 08:55 UTC≈16,700 views15 reactionsread 3 September 2026
Photo

萌哩:聚合 Pixiv 与 X 的二次元美图站,支持最高 4K 原图下载 萌哩(moely)是一个专门收集二次元插画的图片站,内容精选自 Pixiv 和 X(Twitter),经过人工筛选后收录。每张图片都会保留画师、作品描述、标签和原始来源,支持最高 4K 分辨率原图下载。网站有随机探索功能,再也不怕发现不了美图了~ 网站特性 🖼响应式瀑布流设计,图片灯箱效果 🏷通过标签筛选图片 🔣PWA(渐进式网络应用程序)支持 🎁支持将图片添加收藏,收藏列表云端同步 🔎关键词搜索功能,支持多参数搜索 萌哩官网 | TG频道

15

18 Aug 2026, 07:51 UTC≈2,050 views11 reactionsread 3 September 2026

🎁 Codex 额度或将在今晚再次重置! Codex 负责人 Tibo 再次发布神秘暗示,并魔改了 ABBA 经典歌曲《Gimme! Gimme! Gimme!》: “Gimme, gimme, gimme Codex after midnight Won’t somebody make these failing tests all go away? Gimme, gimme, gimme Codex after midnight Ship it through the darkness by the start of the day” 其中反复提到 “Codex after midnight”。结合此前多次 Codex 额度重置,以及 Tibo 在突破 1000 万活跃用户后预告的 surprise,今晚或许又要有新的额度福利 👀 目前尚未正式确认,蹲一个午夜后的惊喜。 #Codex #Quota #Predict

11

10 Aug 2026, 23:22 UTC≈2,290 views11 reactionsread 3 September 2026
Photo

Photo, posted without a caption

11

10 Aug 2026, 23:19 UTC≈1,990 views11 reactionsread 3 September 2026
Photo

Y2A-Auto:YouTube 视频下载、翻译到上传全流程自动化 🆕 Y2A-Auto 是一款开源视频自动化处理工具,可以完成 YouTube 视频下载、字幕获取与翻译,并通过 AI 自动生成视频标题、简介等发布信息,将原本需要手动完成的多个步骤整合成自动化工作流。 处理完成的视频支持自动上传至哔哩哔哩、AcFun 等平台,适合拥有转载授权或处理自有视频内容时批量使用。使用第三方视频素材前,需要确认原作者授权及对应平台的版权规定。 💻 GitHub 🌿Ai一线 · 宇宙自然 · 油画小馆

11

10 Aug 2026, 23:14 UTC≈1,430 views13 reactionsread 3 September 2026
Photo

claude-video:让 Agent 同时理解视频画面和声音 claude-video 是一个面向视频分析场景的开源项目,不只是把视频转成文字,而是让 Agent 同时参考画面、语音和视频上下文进行理解。 使用时可以直接提供 YouTube 链接,让模型基于完整视频内容做总结、分析和问答。 相比只依赖字幕或语音转写的方案,这种方式更适合处理演示视频、教程、产品发布会和包含大量视觉信息的内容,可减少“只听到声音、看不到画面”带来的信息缺失。 💻 GitHub 🌿Ai一线 · 宇宙自然 · 油画小馆

13

10 Aug 2026, 22:57 UTC≈1,160 views11 reactionsread 3 September 2026
Photo

豆包开始对酒店订单“抽佣”,综合费率约 12%😍 据新浪科技报道,从今日起,通过豆包入口跳转至抖音来客成交的酒店订单开始执行独立费率,其中软件服务费为 11.4%,另收取 0.6% 支付手续费,综合扣费约 12%。酒店行业人士确认相关通知属实,意味着豆包推荐并促成的酒店订单已开始单独收取佣金。 抖音生活服务此前发布特定渠道软件服务费政策,明确新规自 2026 年 8 月 10 日起生效,并将“豆包”列入特定成交渠道。软件服务费以用户实付金额及平台通用券等补贴金额为计算基数,具体费率会根据商家、商品、POI 类目及成交渠道等因素确定。 🌿Ai一线 · 宇宙自然 · 油画小馆

11

10 Aug 2026, 22:55 UTC966 views11 reactionsread 3 September 2026
Photo

MonkeyCode 每天免费提供 3000 万 Tokens,内置云端开发环境 🆕 MonkeyCode 是一款面向 AI 编程场景的开发工具,目前每天提供最高 3000 万免费 Tokens,支持 DeepSeek V4 Flash、Kimi K2.5、MiniMax M2.5、Qwen 3.5-Plus 等多款模型,可用于代码生成、项目开发等任务。 除了模型调用,MonkeyCode 还内置云端开发环境,可以直接创建和运行项目。例如使用 AI 开发网站后,可通过公网地址直接预览运行效果,将模型调用、代码编写和部署预览集中在同一套工作流中。 MonkeyCode官网 微信公众使用教程 🌿Ai一线 · 宇宙自然 · 油画小馆

11

10 Aug 2026, 22:52 UTC921 views11 reactionsread 3 September 2026
Photo

Meta 推出 300 亿参数 Muse Glimmer,单张消费级 GPU 即可本地运行 🆕 Meta 发布 300 亿参数开放权重模型 Muse Glimmer,并采用 Apache 2.0 许可证开放。该模型针对本地 Agent 工作流进行优化,可在配备单张消费级 GPU 的 Mac 或 PC 上运行,覆盖本地智能体、函数调用、本地编程以及 LLM 自动化评估等应用场景。 Muse Glimmer 的重点是降低 Agent 模型的本地部署门槛,让更多智能体任务无需完全依赖云端模型运行。Meta 还计划在未来几天陆续提供llama.cpp、MLX 和 ExecuTorch 集成,进一步完善桌面端及边缘设备的部署支持。 Meta AI 🌿Ai一线 · 宇宙自然 · 油画小馆

11

10 Aug 2026, 22:49 UTC966 views11 reactionsread 3 September 2026
Photo

HeyGen 3 个月免费试用码流出,另有 HP OMEN 官方领取渠道 HeyGen 近期出现一组 3 个月免费试用兑换码,流传的代码格式为 HP3FREE-TG29P,其中 HP3FREE- 被认为是活动代码前缀。相关信息同时指向 HeyGen 与 HP OMEN 的合作活动,主要面向印度区用户,实际能否兑换及账号资格以 HeyGen 系统验证结果为准。 除了兑换码外,HeyGen 目前还有 HP OMEN 合作活动页面。有需求的用户可以直接通过官方渠道查看 3 个月免费权益的领取条件、适用地区及活动状态,避免使用批量试码或自动化撞码等可能违反平台规则的方式。 ❤️ HeyGen 有 AI 视频制作刚需的兄弟抓紧上车,手慢无! 🌿Ai一线 · 宇宙自然 · 油画小馆

11

Showing the 12 most recent of 23 posts we hold for @FollowBun. 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.

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

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

“Ai一线 | 软件 资讯 新闻” (@FollowBun), 22,504 subscribers as measured 4 September 2026. Telegram Register, tgregister.com/channel/FollowBun.

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.