名称:九门 (2026) 4K 更新 E01 - 24 集 描述:长沙风云再起之时,张启山(陈伟霆 饰)与吴老狗(曾舜晞 饰)强强联手,携手霍仙姑(陈瑶 饰)与九门诸人共赴冒险奇局。一桩401部队的神秘失踪事件,牵出百年尘封的惊天秘辛。生死抉择、兄弟之情、门派担当与家国大义相互交织。九门众人用热血和牺牲,守护家园,共渡难关。 夸克:https://pan.quark.cn/s/a4893e8ccfc6 📁 大小:19GB 🏷 标签:#九门 #剧情 #动作 #冒险 #国剧

Channel
夸克云盘影视资源频道
@Quark_Movies
On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Cite this entry
104,932subscribers
+288 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 100,000–316,228.
Register entry
| Telegram ID | -1001959723113 |
|---|---|
| Type | Channel |
| Username | @Quark_Movies |
| Created | Between 1 April 2023 and 31 October 2023— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 12 August 2026 |
| Measurements held | 9 |
| Confirmed unchanged | 1 time, most recently 12 August 2026 |
| On Telegram | t.me/Quark_Movies |
Topic
Film & TV — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 10 August 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
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 12 Aug 2026, 19:35 | 104,932 | +43 |
| 11 Aug 2026, 17:22 | 104,889 | +28 |
| 10 Aug 2026, 18:26 | 104,861 | +53 |
| 9 Aug 2026, 15:16 | 104,808 | +71 |
| 8 Aug 2026, 18:05 | 104,737 | +41 |
| 7 Aug 2026, 15:32 | 104,696 | +25 |
| 6 Aug 2026, 16:24 | 104,671 | +27 |
| 6 Aug 2026, 05:20 | 104,644 | no change |
| 6 Aug 2026, 05:19 | 104,644 | first reading |
Engagement
283 posts held, back to 6 August 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 17 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 0.3%
- avg views ÷ 104,932 subscribers
- Avg views / post
- 315
- 283 posts measured
- Reaction rate
- 0.277%
- reactions ÷ views · ER floor
- Posts in window
- 283
- of 283 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. It is computed over the 52 of 283 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 12 August 2026 |
|---|---|
| Posts held | 283 (6 August 2026 – 12 August 2026) |
| Views total | 89,059 |
| Reactions total | 50 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Aug 2026, 18:31 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
49 reactions across 43 posts, in 3 distinct kinds. The most used accounts for 49.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 24 | 49.0% | |
| 👍 | 24 | 49.0% | |
| 👎 | 1 | 2.04% |
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 52 of the 283 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 50reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 283 most recent posts we hold, published 6 August 2026 to 12 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
#原盘 #4K #电影 #频道 这是一个夸克频道,专注分享国内、海外高画质热门、经典、新出的电影,以4K、REMUXE/原盘 为主,每日分享。。。。。。。。。 频道地址:@jnjy_5
名称:花开锦绣(2026)4K 臻彩 S01E01 - E10 HiveWeb 杜比全景声 描述:豪爽重情的私盐贩子赵凌虽出身草莽,却心怀壮志,他结识了遭人诬陷私通的世家名媛小姐傅庭芸,被迫一起逃亡,二人历经家族与朝廷的重重考验,与命运抗争,终成传奇良缘。 剧集改编自吱吱同名言情小说《花开锦绣》。 夸克:https://pan.quark.cn/s/0c42957a8693 📁 大小:4GB 🏷 标签:#剧情 #花开锦绣
名称:人鱼(2026)4K 60FPS S01E01 - E16 HIFI声 HiveWeb 描述:就读于职业中学培训部的花季女生苏琳(黄杨钿甜 饰),虽自小被父母忽视,在艰苦环境中长大,但她始终刻苦学习,憧憬未来。为此,苏琳苦练口语并争取到了英文朗诵剧中小美人鱼的角色,却不想遭到同学马娜(段钰 饰)的嫉妒。一次激烈冲突中,她意外掉入地下管道,生死不明。 而此时,与地下管道有关的卫红渠案也曝露在公众视野中,霎时,案件的侦查与苏琳的命运紧紧交织在一起。 地下管道中的苏琳恐惧无助,但从未放弃希望。与此同时,邻居民警顾浩、萍水相逢的同校女孩姜庭(何思甜 饰),也始终心系她。 当苏琳终于在流浪汉文森特(赵健 饰)的帮助下重返地面时,却撞见了案件的真相。善良的苏琳无法袖手旁观,她尽全力协助警方抓捕罪犯。最终,苏琳冲破牢笼,不屈不挠地奔向属于她的天地。 夸克:https://pan.quark.cn/s/1224845280b8 📁 …
名称:H//PE Princess — 17.7 (Japan Deluxe Edition) (2026-08-12) [FLAC 24bit/96kHz] 描述:H//PE Princess《17.7》日本豪华版,日韩合作女团,嘻哈电子融合流行,曲风冷冽锐利。24bit‑96kHz高解析,收录原版曲目,额外附赠日语混音与加曲。 夸克:https://pan.quark.cn/s/4f8a0f7dc416 📁 大小:399MB 🏷 标签:#无损音乐 #音乐 #kpop
👍1
名称:器子(2025)4K 臻彩MAX+ 60FPS DTS环绕声 内嵌简英 描述:女儿在三个月大时失踪,疑似被贩婴集团偷走,妻子过度自责后自戕,他为追查真相反被诬陷入狱,出狱后查出女儿是落入活摘器官集团,成为被取走心脏的「器子」。他悲愤难当,对犯罪集团连翻展开以暴制暴的复仇行动,全力营救作为「器子」的女儿。 夸克:https://pan.quark.cn/s/38b104da4642 📁 大小:12.82G 🏷 标签:#器子 #动作 #剧情 #犯罪
名称:斩神之凡尘神域 第二季(2026)4K 10bit 更至EP10 描述:沧南危机解决后,林七夜完成津南山为期一年的守夜人集训考核,成为了正式的守夜人后,重回136小队,与伙伴再度开启一场与古神教会的崭新较量……新的西方邪神亮相,人类天花板齐聚沧南,一场巨大的灾难风暴正悄然酝酿成型。 夸克:https://pan.quark.cn/s/82667cc0bdf6 📁 大小:1G/集 🏷 标签:#斩神 #斩神之凡尘神域 #动作 #动画 #奇幻
名称:阳光照耀青春里 (2025) 描述:年轻有才的程序员何立为(肖央 饰)供职于家园软件公司,并独自开发了一款游戏。他的偏执和作为扰乱了公司的融资计划,被公司送进了“青春里”精神康复院。 夸克:https://pan.quark.cn/s/607800c90d9e 📁 大小:NG 🏷 标签:#剧情
名称:李志 2004 04《被禁忌的游戏》FLAC 描述:2004.04《被禁忌的游戏》 夸克:https://pan.quark.cn/s/ab0faefbebf2 📁 大小:182MB 🏷 标签:#无损音乐 #音乐 #李志
名称:擦边短剧:奇遇人生&面具游戏(完整版) 描述:喜欢就存 每日更新 | 2026年8月12日抖音快手红果新剧已送达! 每天同步更新全网最新短剧,频友第一时间看新剧! 夸克:https://pan.quark.cn/s/7865442153d6 📁 大小:N 🏷 标签:#短剧 #最新短剧 #合集 #擦边短剧 #短剧榜 #Ai短剧 #动漫短剧
名称:熊出没·原始时代 (2019) 描述:熊大熊二光头强意外穿越回恢宏的石器时代,在原始部落与猛犸象、剑齿虎等一众奇特生物开启了眼界大开的奇幻之旅!原始时代瑰丽非常却又危机四伏,熊强三人组与一只可爱狼女一路相伴,笑料百出。原始部落纠葛不断,女族长竟对光头强情愫暗生……面对凶猛狼族的步步紧逼、原始人类的不断质疑、自然危机的全面爆发,熊强究竟何去何从?他们又能否回归现代?一场关于守护与成长、爱与勇气的冒险,拉开序幕…… 夸克:https://pan.quark.cn/s/5e755e81b6c9 📁 大小:NG 🏷 标签:#动漫 #动画
名称:2026年8月12日 短剧更新目录13 描述:1.师妹修炼我成仙(135集) 2.双生契约山河篇(64集) 3.我家王妃怀里藏着万能空间(100集) 4.硬核老妈,恋爱脑儿子乖乖认栽(68集)张火丁&张柏基&谢帅&红中 5.这个乞丐天下无敌(99集)张闻宇&江路祺&陈湧泉&大卫 6.重生八零:离婚干大事(80集)梁小陌&李随意&悟禅 7.三年错爱,追妻复燃(102集) 8.请妖皇赴死,续我华夏三千年(59集)AI短剧 9.灵语契约(62集) 10.老公你怎么变成了我的老板(55集)周煜枫&陈馨雨&大松 11.和离当天,我把侯府账本挂上城门(70集) 12.高冷将军暗恋我藏不住了(58集) 13.冬隅手记:屿见清欢胜长安(60集)吴炫汶&李乐新 夸克:https://pan.quark.cn/s/6772550660b1 📁 大小:N 🏷 标签:#短剧 #最新短剧 #合集 #擦边短剧 #短剧榜 #Ai短剧 #动漫短剧
Showing the 12 most recent of 283 posts we hold for @Quark_Movies. 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 — 182,746 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
Republishes
Channels on the register whose posts this channel has forwarded.
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 2 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.
Named by
Channels on the register whose posts name this channel's handle.
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.
“夸克云盘影视资源频道” (@Quark_Movies), 104,932 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/Quark_Movies.
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.