Channel
@cryptodiffer
On this record: Also posting the same content · Growth · Engagement · What this channel posts · Posts · Posts edited after publishing · Citations · Telegram's recommendations · Cite this entry
24,001subscribers
-64 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1001164439333 |
|---|---|
| Type | Channel |
| Username | @cryptodiffer |
| Description | Essential crypto news and market updates. Subscribe to The Differ — free weekly recap cryptodiffer.beehiiv.com/subscribe Reach Us @natecryptodiffer Twitter x.com/CryptoDiffer Lite t.me/CryptoDifferLite 🗣 Official Public Chat t.me/+WTlxau7ntrkUOEx1 |
| Created | 9 February 2018 — measured — cross-checked against a third-party dataset (ext.tg_channel) |
| 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/cryptodiffer |
This channel’s posts match, word for word or near enough, posts on 376 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.
Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.
326 more channels are in this same group but not listed individually here.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 12 Aug 2026, 12:18 | 24,001 | -11 |
| 11 Aug 2026, 09:16 | 24,012 | -4 |
| 10 Aug 2026, 10:51 | 24,016 | -6 |
| 9 Aug 2026, 12:01 | 24,022 | -9 |
| 8 Aug 2026, 11:33 | 24,031 | -11 |
| 7 Aug 2026, 08:13 | 24,042 | -16 |
| 6 Aug 2026, 11:23 | 24,058 | -7 |
| 6 Aug 2026, 02:03 | 24,065 | no change |
| 6 Aug 2026, 01:07 | 24,065 | first reading |
77 posts held, back to 4 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 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.
| Window | Rolling 30 days · latest post in window 12 August 2026 |
|---|---|
| Posts held | 77 (4 August 2026 – 12 August 2026) |
| Views total | 222,250 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Aug 2026, 22:42 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.
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. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Miden Introduces Privacy-Focused USDCx Stablecoin Ahead of Mainnet Zero-knowledge blockchain Miden is preparing to launch USDCx, a privacy-focused stablecoin backed 1:1 by Circle’s USDC through its xReserve infrastructure. USDCx will allow users to hold and transfer stablecoins without publicly exposing balances, counterparties or transaction histories, while Miden’s selective-disclosure system enables users to rev…
Fidelity Plans to Add Staking and Quarterly Payouts to $898M Ethereum ETF Fidelity is preparing to add Ethereum staking and quarterly cash distributions to its Fidelity Ethereum Fund (FETH), which currently holds around $898M in net assets. Under normal conditions, FETH could stake up to 100% of its ETH, while keeping enough assets available for redemptions, expenses and liquidity needs. Fidelity would retain 85% …
DAOs are sitting on $7.5B, and how they store it splits them into two camps Single-token treasuries keep almost everything in their own coin. Uniswap holds $1.05B, mostly UNI. That looks great when the token is up and becomes a trap when it is not, because the treasury and the token crash together. Diversified treasuries spread the risk instead. Mantle leads at $1.59B across multiple assets, and 310 DAOs now store …
Fed Injects $5.179B Into Financial System Through Treasury Purchases The Federal Reserve Bank of New York is conducting a $5.179B Treasury bill purchase operation today, August 12, as part of its routine reserve-management program. The purchases target Treasury bills maturing between September and December 2026 and are designed to maintain ample bank reserves and support smooth functioning of short-term funding mar…
Lovable Raises $400M in Series C at $13.3B Valuation, Accelerating AI Coding Expansion Stockholm-based AI coding startup Lovable has raised $400M in Series C funding at a $13.3B valuation, led by Menlo Ventures and co-led by EQT’s Scaleup Europe Fund. Lovable says users have created 60M+ projects, while Lovable-built apps now generate 900M+ monthly visits. The platform is used by nearly two-thirds of the Fortune 50…
BitGo Adds a Quantum Risk Score for Bitcoin Wallets BitGo rolled out quantum risk controls for Bitcoin wallets, led by a Quantum Risk Score that flags which addresses have public keys already exposed on-chain. Exposed public keys are the weak point a future quantum computer could target. Alongside guided address remediation and safer UTXO defaults, the score lets institutions migrate funds before any such threat ex…
Kalshi and Blanket Bring Hedging to Small Businesses Kalshi teamed up with Blanket, an AI tool built by economist Lauris Zminsky, that helps small businesses hedge real-world risks using its prediction markets. Describe a risk like a hurricane, a fuel-price spike or an unusually warm winter, and Blanket's AI surfaces Kalshi yes/no markets that could offset the loss. Blanket only recommends contracts and never execu…
Bitget launches $300M fund to back quant firms Bitget Institutional has rolled out Project Archimedes, a $300M capital program aimed at quantitative trading firms, asset managers and market makers. The money splits into two tracks. A $100M Capital Provider Program funds emerging quant firms running market-neutral strategies, with returns shared under an agreed structure. A $200M Interest-Free Lending Program gives …
Solana RWA Ecosystem: Third in Size, First in Trading Everyone argues who leads RWA. By total value it is still Ethereum. But tokenized stocks tell a different story. Solana holds just 23% of tokenized-stock market cap, yet settles 95-97% of all on-chain trading volume. Others hold the shares. Solana trades them. The whole Solana RWA market is up 6.8x in a year to $2.35B, led by BlackRock's BUIDL, with a wild mix …
River AI Raises $1.1B to Build a Personal AI Stack River AI, the two-month-old startup from xAI co-founder Igor Babuschkin, raised $1.1B across seed and Series A, one of the largest rounds for any company founded this year. The round was led by General Catalyst and AMP, with strategic checks from Nvidia and AMD plus Y Combinator and Temasek. River is building personalized AI that users and organizations own and con…
Crypto.com Launches Tokenized US Stock Derivatives Crypto.com rolled out derivatives tracking 1,500 US stocks and ETFs, including Apple, Tesla and Nvidia, offering synthetic price exposure with trades from just $1, around the clock. Issued by Foris Capital and settled through broker Alpaca, the products are live for users in the EEA and approved markets. Holders get no voting rights, only dividend-equivalent adju…
Whatnot Raises $545M Series G at a $20B Valuation Live-shopping marketplace Whatnot closed a $545M Series G at a $20B valuation, roughly double the $11.5B it was worth after its Series F last October. The round was led by ICONIQ, Lightspeed and Avra, with returning backers including Andreessen Horowitz, Y Combinator, DST Global and Alphabet's CapitalG, plus new investors like Kleiner Perkins. Whatnot has now raised…
Showing the 12 most recent of 77 posts we hold for @cryptodiffer. 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.
@cryptodiffer edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
Citation-graph rank — 38,163 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.
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.
Named by 7 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.
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.
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
This channel appears in 3 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
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.
“CryptoDiffer News” (@cryptodiffer), 24,001 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/cryptodiffer.
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.