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Paradigm engagement report

@paradigm - 1.5M followers on X

Measured over 4 original posts from a 30-day window, last computed on September 1, 2026.

Engagement

Per follower
0.023%
of 1.5M followers
Per impression
0.39%
91K views on a typical post
Reach
6.00%
of its followers see a post
Typical post
354
interactions (median)
Saved
0.167%
152 bookmarks on a typical post
Posting rate
0.47/day
active 27% of days
Peak time
16:00 UTC
Tuesday

Early reading. We have captured 4 original posts for this account, below the 8 we require before treating a median as settled. The numbers above describe what we have seen so far, not a finished profile of the account.

A typical post picks up 354 interactions against 1.5M followers, an engagement rate of 0.023%. Posts are seen about 91K times each, and 0.39% of those impressions turn into an interaction. That is about 5.97% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.47 posts a day over the last 30 days, though only 27% of days saw any activity at all. Most posts go out around 16:00 UTC, and Tuesday is the busiest day of the week. Of the 4 posts sampled, 50% carry an image or video and 50% link out. The account's strongest tracked post pulled 12K interactions, about 31x its own typical post. Only 4 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.

Measured over 4 original posts from a 30-day window, last computed on September 1, 2026.

Where this sits in the catalog

At 0.023%, Paradigm sits above the 25th percentile of the 36,960 accounts in this comparison. That places it in the below the median band, which runs 0.012% to 0.08%.

p100.002%
p250.012%
p50 (median)0.08%
p750.435%
p902.10%
p99159.8%
Engagement rate as a share of followers, across the 36,960 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 106,518 times apart and a linear axis would flatten everything below the median into a single point.
Show the percentile table
Engagement rate percentiles
PercentileEngagement rate
10th percentile0.002%
25th percentile0.012%
50th percentile0.08%
75th percentile0.435%
90th percentile2.10%
99th percentile159.8%

This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built

Posting timing

This account posts most often around 16:00 UTC, and Tuesday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.

Engagement by hour posted, UTCTwenty-four bars, one per UTC hour. Each bar shows how posts published in that hour compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest hour: 16:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 6%Busiest hour: 16:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%51K
01:00 UTC-2%52K
02:00 UTC-3%51K
03:00 UTC-4%54K
04:00 UTC-6%44K
05:00 UTC-4%42K
06:00 UTC-4%49K
07:00 UTC-5%53K
08:00 UTC-4%61K
09:00 UTC-3%70K
10:00 UTC-2%73K
11:00 UTC-3%79K
12:00 UTC-2%87K
13:00 UTC-2%96K
14:00 UTC-4%99K
15:00 UTC-2%102K
16:00 UTC-3%99K
17:00 UTC-2%92K
18:00 UTC-1%85K
19:00 UTC-2%80K
20:00 UTC-1%75K
21:00 UTC-1%67K
22:00 UTC-2%58K
23:00 UTC-1%52K
Engagement by day of weekSeven bars, one per weekday, Sunday first. Each bar shows how posts published on that day compare with their own authors' median engagement. Bars above the centre line ran higher than the median, bars below ran lower. A marker flags Busiest day: Tuesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 5%Busiest day: Tuesday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%233K
Monday0%292K
Tuesday-3%284K
Wednesday-1%253K
Thursday-2%246K
Friday-3%255K
Saturday+3%229K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Best tweets

  • Sep 25, 202531x their median

    Announcing Credit — an automated, undercollateralized lending system built on stablecoins. Live since December 2024, it has issued 175,000+ loans to 100,000+ unique borrowers worldwide We raised $6.6M led by Paradigm, with Nascent and strategic angels, to scale and expand Credit https://t.co/BJjxG2aa7P

    5.7K3.6K2.4K304419K viewsView on X
  • Feb 18, 202634x their median

    Introducing EVMbench—a new benchmark that measures how well AI agents can detect, exploit, and patch high-severity smart contract vulnerabilities. https://t.co/op5zufgAGH

    8.7K1.3K1.1K8422.6M viewsView on X
  • May 9, 202624x their median

    Hermes Agent is now #1 on the Global @OpenRouter token rankings. While our journey together has just begun, we'd like to take this opportunity to thank our contributors, supporters, and users for all they have done to get us this far. https://t.co/kA4hPJHKNM

    7.1K7004282853.0M viewsView on X
  • Jul 22, 202621x their median

    I solved 6 open Erdős problems in 5 days, using @OpenAI GPT-5.6 Sol. I have a math background, but the Codex workflow I used does not require deep mathematical knowledge. Here’s exactly how I approached it, including my prompts 🧵

    6.3K6731262101.6M viewsView on X
  • Apr 13, 202620x their median

    This is the story of Hyperliquid, the most profitable startup per employee on earth, told from a guarded office in Singapore. Last year, its team of 11 generated $900 million in profit. It's 3 years old, has never taken a dollar of venture capital, and is beginning to change how century-old markets work. Its founder, Jeffrey Yan (@chameleon_jeff), had never taken a physics class when he picked up a textbook at 16. Two years later, he won gold at the International Physics Olympiad. In 2019, he started trading with $10,000 from a living room in Puerto Rico—working off a television because he didn't own a monitor. Within 3 years, he was running one of the largest anonymous crypto trading firms. Then he shut it down. Yan was rich and free, but he had spent years inside crypto, watching it betray itself. Bitcoin's central premise was decentralization. Yet the biggest exchanges were centralized. Crypto kept reintroducing the dependence on trust it was built to eliminate. He set out to create what should have existed. Hyperliquid is a blockchain with a trading exchange on top, and anyone can build on it. Yan's vision is to house all of finance. In 3 years, it has done over $4 trillion in volume. And in the past few months, it has begun to outgrow crypto. Markets for oil, silver, and the S&P 500 now trade on Hyperliquid around the clock, weekends included, and are growing roughly 40% week on week. When the US and Israel bombed Iran on a Saturday in February, Hyperliquid was the venue traders turned to. Hyperliquid's success has cost Yan his freedom. He works out of a secret office in Singapore and cannot travel without two bodyguards. Even the team's housekeeper doesn't know what they do. In January, @domcooke spent a week at their office. Read his profile on Yan and @HyperliquidX below.

    5.3K9854284943.8M viewsView on X
  • Dec 9, 202517x their median

    Tempo’s testnet is live! Any company can now build on a payments-first chain designed for instant settlement, predictable fees, and a stablecoin-native experience. Tempo has been shaped with a wide group of partners validating real workloads including @AnthropicAI, @Coupang, @DeutscheBank, @DoorDash, @Lead_Bank, @mercury, @nubank, @OpenAI, @Revolut, @Shopify, @StanChart, and @Visa. Since our announcement, @brexHQ, @Coastal, @crossriverbank, @deel, @faire_wholesale, @Figure, @GustoHQ , @Kalshi, @Klarna, @Mastercard, @Payoneer, @withpersona, @tryramp, and @UBS have also joined as design partners. Dedicated payment lanes, stablecoin gas, deterministic finality, a built-in stable asset DEX, and programmable smart accounts are all live on testnet. If you’re building or modernizing payment flows, you can start integrating and testing today.

    4.6K8917683801.2M viewsView on X
  • Dec 2, 202514x their median

    Kalshi raised $1B at an $11B valuation. A decade ago, only a few thousand people knew what a prediction market was. Eighteen months ago, most prediction markets were banned - until we overcame the government to set them free. Over the past seven years, our community has opened up an entirely new category. Today, Kalshi is trusted, used, and loved by millions of people. It’s a part of everyday culture, and it’s driving one of the most important shifts in consumer behavior in recent history. The time has finally come for prediction markets to achieve their full potential and we are intent on making that happen. To all the believers and the early adopters: thank you.

    4.1K3885874108.6M viewsView on X
  • Feb 4, 202614x their median

    new from paradigm: we are building a tool for exploring prediction market data try it out today. I bet you'll find new markets you never knew existed https://t.co/HtDBWtFoys

    4.8K34421073374K viewsView on X
  • Sep 4, 202511x their median

    Introducing @tempo A payments-first blockchain incubated by Stripe and Paradigm

    2.8K2294273181.9M viewsView on X
  • Mar 18, 20269.2x their median

    Tempo Mainnet is live! Starting today, anyone can build on Tempo through our public RPC endpoints. Alongside mainnet, we’re introducing the Machine Payments Protocol, an open standard for machine payments. https://t.co/Ax2qEIBcwp

    2.6K348311282743K viewsView on X

Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.

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Reading these numbers

A typical post picks up 354 interactions against 1.5M followers, an engagement rate of 0.023%. Posts are seen about 91K times each, and 0.39% of those impressions turn into an interaction. That is about 5.97% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.47 posts a day over the last 30 days, though only 27% of days saw any activity at all. Most posts go out around 16:00 UTC, and Tuesday is the busiest day of the week. Of the 4 posts sampled, 50% carry an image or video and 50% link out. The account's strongest tracked post pulled 12K interactions, about 31x its own typical post. Only 4 original posts have been captured so far, fewer than the 8 posts we want behind a median before treating it as settled. Read the figures above as an early measurement of this account, not as a finished profile of it.

What is Paradigm's engagement rate on X?
Paradigm (@paradigm) has an engagement rate of 0.023%, based on the median interactions across 4 original posts from the last 30 days against 1,524,352 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.023%, Paradigm sits above the 25th percentile of the 36,960 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
Does @paradigm have real engagement?
There is not yet enough sample to rank this account against others of its size.
When does @paradigm post?
Most posts go out around 16:00 UTC, and Tuesday is its busiest day, at roughly 0.47 posts per day across the measured window.

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