Channel
@crypto404x
On this record: Topic · Growth · Engagement · Reactions · Posts · Cite this entry
318subscribers
-8 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1001444875042 |
|---|---|
| Type | Channel |
| Username | @crypto404x |
| Created | Between 1 April 2019 and 31 October 2021 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 11 October 2026 |
| Measurements held | 6 |
| Confirmed unchanged | 1 time, most recently 11 October 2026 |
| On Telegram | t.me/crypto404x |
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 22 September 2026 and assigned it the closest of 31 fixed categories, at 49% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Oct 2026, 06:21 | 318 | -1 |
| 29 Sept 2026, 23:41 | 319 | -2 |
| 7 Sept 2026, 09:40 | 321 | -2 |
| 16 Aug 2026, 06:17 | 323 | -3 |
| 7 Aug 2026, 05:18 | 326 | no change |
| 7 Aug 2026, 05:09 | 326 | first reading |
12 posts held, back to 17 December 2024 — 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 12 posts for this entry, the most recent from 5 April 2025. An engagement rate over an empty window would be a number about nothing.
73 reactions across 12 posts, in 5 distinct kinds. The most used accounts for 56.2% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 41 | 56.2% | |
| 👍 | 18 | 24.7% | |
| 👏 | 6 | 8.22% | |
| 🔥 | 4 | 5.48% | |
| 😢 | 4 | 5.48% |
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 12 of the 12 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 73 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 12 most recent posts we hold, published 17 December 2024 to 5 April 2025, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Hi I am still doing AI trading system, 24/7 I need some brainstorm, maybe some of u have some ideas how to train or have some experience or just wanna cooperate (idk how ) Feel free to write here smth
❤2
Still working on it. I am really stuck here. It's much more complicated then just teach model where to entry on chart. Right now I took my pretrained model which know where to entry on chart. And teaching an agent to use this model. It should trade on 5m chart and also look at 1h chart at the same time. Pretrained giving signal to entry - agent entering trade with random sl tp. At the end it will understand whic…
👏6🔥3
Sounds crazy for me. But. Right now to trade it as RL for me will takes 276 days 🥲 and I will not be able to use my PC ofc. I will try to find a way how to optimize it. Need to make it at least 10 times faster somehow
❤4👍1
Also thinking about RL (reinforcement learning) Now my model know when to enter long or short, but SL/take profit is fixed what is problem. RL can fix this. I can use my model which know when to enter short or long and train it as RL. RL it's like when u give freedom to AI and AI will go trade past 3year of btc for example 1000 times. You give to AI a mission to achieve for example best profit with low dropdown. …
❤2👍2
I facing a difficulties. Ai understand logic perfectly and I like it. but at the end seems it's not always work profitable. I mean if season changes then need confirmation from big timeframe like 1h or 4h. But for it need second pertained AI model. Thinking now how to train second one, with which dataset and how to make it work together with many trades yearly. Coz if I add 4h timeframe as filter - will be less than…
❤4🔥1
but seems like i find a best way to use model. this strategy no one other bots can do. but because of computer vision, Ai can. this one - model entering the trade with stop loss ( lets say in long). but it will not put take profit order. model will hold the position until model will not feel its time to close position coz feels time for short. on 5m chart from 1000$ in 1 year it did 3549$ after comission. with maxi…
❤7👍1
i am continue to improving dataset. more dataset = better model (i hope) and trying different strategies. different stop loss take profit and so on. there is really a lot of parameters need to check and every parameter takes many hours to see the results
❤3
so far best results i achieved on standart stop loss take profit trade strategy on 5m 1year chart is around 30% yearly clear profit after 450 trades. with maximum dropdown -30%. it seems good actually, but point is - profit is 30% yearly for this strategy. but without comission it would be 200-250% yearly. i mean if started balance 1000$ - after 1 year should be 1300$. model trading nicely with good win rate. but c…
❤5👍2
hi, model getting smarter and smarter. i am very proud to see that its really understand what i wanna teach it. u can see example how its trading now during backtesting. first chart = 5m chart second chart = 15min chart to help not to long on top or short the bottom still because not enough dataset sometimes entering not really on time what cause stop loss. but with bigger dataset it should not make that mistakes
👍10❤2
If you are interested, Right now on backtesting model doing stable around+50-60% profit yearly. But after commission and slippage at the end it earn almost zero. Now is like commission farmer bot, for Binance can be good, but for us no profit 🥲
😢4👍1
Hard. Very hard. Problem is - I am using innovation method which is no one used yet. My method based on computer vision, AI looking at chart (picture) same as human do. All others competitors other bots using old system (even if they train AI) they are using method which is work with numbers in bot head. Example: Their system = model know (only numbers) BTC open price, current price, indicators, and if price cro…
❤5
here is example how model trade right now and when doing entries. its not perfect yet but i really like. with more dataset model should be smarter and make better entries. and yes SL and TP not good on charts coz as i said later will set up when model will be ready. and triangles at the end of chart meaning only that entry short or long. i mean the point where exactly the triangle doesnt mean entry there. entry a…
❤7👍1
Showing the 12 most recent of 12 posts we hold for @crypto404x. 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.
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 11 October 2026 — this entry's latest reading, not the date you are reading this.
“404 (x) Crypto” (@crypto404x), 318 subscribers as measured 11 October 2026. Telegram Register, tgregister.com/channel/crypto404x.
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.