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vitalik.eth (@VitalikButerin) X analytics
@VitalikButerin
I choose balance. First-level balance. mi pinxe lo crino tcati https://t.co/gCQrmCby7P
@VitalikButerin has 8M followers, a median of 337.5K views per post and a 0.60% engagement rate.
Based on 30 recent original posts (high confidence). Updated October 7, 2026.
At a glance
Key stats
- Followers
- 8M
- Median views per post
- 337.5K
- Average views per post
- 433.9K
- Engagement rate (by views)
- 0.60%
- Original posts per week
- 3.7
- Average engagements per post
- 2,588
Engagement grade
Developing
This is near the lower benchmark range for accounts with 1M+ followers.
Profile score
81/100
- Profile completeness100
- Audience shape100
- Engagement25
- Consistency100
- Positioning clarity79
Monetization
Estimated X creator earnings
$52–$124 in the last 30 days
From 10.3M views on @VitalikButerin's original posts in the last 30 days.
Rewards eligibility: likely
Rough estimate. X publishes no payout rate, so this assumes about $5–12 per 1M original-post impressions from reported creator payouts. Only Premium viewers’ impressions count, so real payouts can be much lower.
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Growth
Follower growth
Tracked by Xholic since July 20, 2026.
Timing
Best times to post
When @VitalikButerin's recent posts performed best (UTC).
- #1 slot
8:18 PM
Monday · UTC
- #2 slot
8:12 PM
Tuesday · UTC
- #3 slot
8:23 PM
Wednesday · UTC
What worked
Top recent posts
- 01
@VitalikButerin ·
The cryptographic world computer: https://t.co/LF2JGU38Rx My attempt to express in somewhat concise terms the true meaning of basically everything planned to happen to Ethereum starting from the fork after Hegota. It's really not just a blockchain anymore. It's a hybrid architecture that combines together blockchains and modern cryptography, to enable much more powerful properties. FOCIL, EIP-8288, Lean consensus, state management, formal verification, advanced mempool improvements (including privacy), and the longer-term specter of obfuscation all mentioned.
- 592Replies
- 990Reposts
- 5.7KLikes
- 1.5MViews
4.2x average engagementShares a linkLong post (over 200 characters)Posted Sun 10:00 UTC - 02
@VitalikButerin ·
It's an increasingly common take that AI hacking means cybersecurity is doomed. I disagree. I think cybersecurity is naturally defense-favoring once people get their shit together. And anyone who continues to hold cryptocurrency (including me, ~90% of my net worth) is implicitly making that bet. Here's why I am making that bet. First, the oversimplified punchy one-line statement: If AI can prove Navier-Stokes and FLT, then AI can prove the statement "this program is secure" as a mathematical theorem. Even if the program is very complicated. Now, the nuance: (See also: https://t.co/6YPWgVT7rO ) The word "secure" is hiding all kinds of skeletons in the closet in terms of what it actually means. What does it mean for Signal (the encrypted messenger) to be "secure"? The most basic definition you might think of is: no one who doesn't hold the recipient's secret key can read the contents of the message. But: * Did you remember to include _other_ critical forms of security? Can the adversary forge messages? Can the attacker prevent messages from reaching the recipient? Can they cause your client to crash by sending malformed messages? * Have you made sure that your model of the adversary includes attackers that interfere with the protocol actively and not just passively? And attackers that interfere by replaying messages to you or the recipient that either of you sent over the wire at any point earlier? * What if the adversary hacked (or _is_) the Signal server? * How did you learn which public key belongs to the recipient in the first place? What if that process was tampered with? * What if your device gets hacked at some point in the past or future - is your message still safe then? * What if your key leaks because of a bug in your operating system? Or because you got a bugged version of the Signal client? Or what if the database is corrupted? * Or the libraries, interpreter or compiler of the programming language you wrote it in? * What if your key leaks because tiny perturbations in perceptible signals generated by the hardware leak mathematical relationships that can extract the key a few hundredths of a bit at a time? * Are you hiding the *size* of the payload? Does that matter? * You're definitely not hiding the identity of the sender and the recipient, and the exact time each message was sent (think: not just time-of-day, but also time deltas between one message and the next). Is that not enough to deduce a lot of important facts about what relationships you have, and what *kinds* of conversations you are having? So ... even definitions can be over a thousand lines of code, and need deep careful thought to figure them out. Working on making definitions more human-readable is of extreme importance - it's perhaps the only "high-level language" that matters right now. But even still, even despite all of the above, for security-critical components, the definition is a much smaller attack surface than the implementation. Verifying that the definition is adequate is a much more tractable task than scanning over the code directly - and can become even more tractable with better tooling. Definitions are also _additive_: if two groups have two different definitions A and B, then, well, you can just prove that the program satisfies both A and B. Code is not additive in this way: if a program is A + B, a bug in A _or_ B can sink the whole thing. Definitions are additive. And if you can't satisfy A and B at the same time, you've isolated the most important philosophical issue for your project to spend its next few weeks grappling with. Sometimes, definitions are not much smaller than the implementation - UI components might be one example. But for many of the most critical components - message-passing protocols, sandboxes, cryptography like SNARKs and FHE - the asymmetry is real. Historically, a large class of failures with this approach have come from people only verifying a small portion of their code, that they self-declared to be the security-critical portion, and ignoring the rest - and it turns out that something in the rest of the code is security-critical too. This was reasonable back when verification was difficult and scarce. The solution today: sorry, you have to verify over literally your entire program, including database, networking, any caching layers, everything. Modern AI can do it. So it's not about "the good guys find all the vulnerabilities before the bad guys do" - that could maybe work too, after all a finite program only has a finite number of vulns, but it's riskier - it's specifically an asymmetric strategy of making code that is much more resilient in the first place. This is the kind of direction that Ethereum is going in for the next few years. There is no future for blockchains - especially blockchains with scalability and privacy - without doing this. We need to make software actually secure. And we have already made a lot of progress.
- 374Replies
- 424Reposts
- 3.2KLikes
- 813.5KViews
2.1x average engagementShares a linkLong post (over 200 characters)Posted Wed 21:00 UTC - 03
@VitalikButerin ·
Also this thing is done now https://t.co/1VFk2f0fZx
- 630Replies
- 298Reposts
- 3.1KLikes
- 875.7KViews
1.9x average engagementShares a linkShort post (under 100 characters)Posted Sun 14:00 UTC - 04
@VitalikButerin ·
Doing a bit of a self-experiment. Goal: use my personal health and travel data to provide personalized diet and exercise recommendations for me, using frontier models but in a way that avoids leaking to them any private information. Strategy: use a local model (Qwen 3.8 Flash Next) to orchestrate, and use powerful remote models as a tool call to benefit from higher-level thinking and knowledge that the local model does not have. Three-layer approach to privacy: Avoid leaking personally identifiable information, or leaking my identity through writing style -> local model writes the queries to the frontier model, not me Avoid leaking who I am through the payment channel -> zkAPI Avoid leaking who I am through networking / IP -> Tor You need all three (and finally we have all three, at least to some extent) A skill file teaches the local model when and how to construct minimally-data-revealing requests to remote models. Use zkAPI-wrapped-with-Tor as a CLI tool. And everything works! I got the recommendations back, info from frontier models helped to improve them. Main deficiencies: * Tor is really not optimized for request-by-request de-linking, which is the only form of network-layer privacy that really makes sense in today's world (long-running identifiers are too fragile). Probably not private enough, and latency 10-100x higher than it could be, at the same time. * The skill file's request construction strategies are definitely far from optimal. * Qwen 3.8 Flash Next is still too slow for comfort. It's comfortably running at 20-30 TPS, but it would only really start to feel fast at 100+ * There is a tradeoff: the more careful you are about what data you give to a remote model, the less it can help you https://t.co/1g81Mp1sWW
Photo on the original post- 399Replies
- 214Reposts
- 2KLikes
- 432.5KViews
1.4x average engagementHas an imageLong post (over 200 characters)Posted Sun 00:00 UTC - 05
@VitalikButerin ·
It's only dead if you give up I'm not giving up on privacy. I'm doubling down. https://t.co/CdLNAiCC9h
- 495Replies
- 378Reposts
- 3.4KLikes
- 568.5KViews
1.4x average engagementShares a linkShort post (under 100 characters)Posted Sat 20:00 UTC - 06
@VitalikButerin ·
Glad to see that Ethereum L1 will have a new strong prediction market contender that is dedicated to decentralization, and being ethical and not corposlop, and to actually trying to do interesting and meaningful things with this class of economic primitive. https://t.co/Rj86ZJl3G4
- 403Replies
- 356Reposts
- 3KLikes
- 850.8KViews
1.4x average engagementShares a linkLong post (over 200 characters)Posted Mon 21:00 UTC
Formats
Content mix
- Text only
- 20%
- With media
- 23%
- With links
- 20 posts
- With hashtags
- 0 posts
Creator style: High-reach broadcaster
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About this data
- Analytics are inferred from public profile and recent post data. They do not include private impressions, profile visits, link clicks, or follower-source data.
- Deleted, protected, unavailable, or rate-limited posts may be missing from the sample.
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