Garry Tan engagement report
@garrytan - 1.1M followers on X
Measured over 118 original posts from a 30-day window, last computed on October 25, 2026.
Engagement
A typical post picks up 311 interactions against 1.1M followers, an engagement rate of 0.027%. Posts are seen about 48K times each, and 0.649% of those impressions turn into an interaction. That is about 4.19% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 18.2 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 16:00 UTC, and Tuesday is the busiest day of the week. Of the 118 posts sampled, 63% carry an image or video, 6% are part of a thread and 38% link out. The account's strongest tracked post pulled 54K interactions, about 174x its own typical post.
Measured over 118 original posts from a 30-day window, last computed on October 25, 2026.
Where this sits in the catalog
At 0.027%, Garry Tan sits above the 25th percentile of the 204,491 accounts in this comparison. That places it in the below the median band, which runs 0.024% to 0.143%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.677% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
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.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 89K |
| 01:00 UTC | -2% | 90K |
| 02:00 UTC | -3% | 88K |
| 03:00 UTC | -4% | 94K |
| 04:00 UTC | -5% | 76K |
| 05:00 UTC | -4% | 75K |
| 06:00 UTC | -5% | 86K |
| 07:00 UTC | -5% | 93K |
| 08:00 UTC | -4% | 108K |
| 09:00 UTC | -4% | 124K |
| 10:00 UTC | -3% | 129K |
| 11:00 UTC | -3% | 141K |
| 12:00 UTC | -3% | 154K |
| 13:00 UTC | -3% | 167K |
| 14:00 UTC | -4% | 173K |
| 15:00 UTC | -2% | 176K |
| 16:00 UTC | -3% | 171K |
| 17:00 UTC | -3% | 159K |
| 18:00 UTC | -2% | 149K |
| 19:00 UTC | -2% | 141K |
| 20:00 UTC | -1% | 131K |
| 21:00 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
Formats this account uses
Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 63% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 38% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 63% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
- 38% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts.
- Its average post runs 302 characters, which falls in the over 280 characters band. Across the catalog, posts over 280 characters run 15% above the same accounts' other posts.
These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.
Best tweets
- Oct 8, 2026174x their median
Intelligence must draw on memory. The mind must not simply compile data — as an algorithm now does more quickly than we can — but recall lived experiences, which contain depths of meaning that only the human soul can recognize, and connect more deeply with the goodness of these experiences. Everything that is good begins “with the Spirit” and thus possesses a breath, a dynamism and a sense of communion that, once experienced, are engraved upon the heart. https://t.co/Ij21tkb3qT
- Sep 29, 2026116x their median
Chief Design Officer @jgebbia officially unveils https://t.co/tMEB6EUmxg, the new online home for the United States of America https://t.co/Mlllz44UaQ
- Oct 18, 202676x their median
notice.. > Delta is blocking AI agents from booking flights > JPMorgan Chase and Charles Schwab block agents from accessing accounts > Yelp requires paid data licensing for agents > Amazon has blocked Grok bot and other shopping agents. the internet is starting to block AI agents that were supposed to do everything for us
- Oct 17, 202669x their median
a comment from 3blue1brown's most recent video https://t.co/qRtVhQylFJ
- Oct 8, 202663x their median
Hello computer. Decompile and distill Grand Theft Auto. Make the game set in my hometown -- use Google Earth to reconstruct it in pixel-perfect detail. Make the character me and have my spawn point be in the mansion I always look at on Zillow. Review my chat memory and make every mission about my hopes and dreams. Make it playable online so my friends can join. When you're done, sell all my video games on Ebay and use that money to fund tokens for my next game.
- Oct 20, 202651x their median
Hardware looks scary until you break it down into small steps. So I built an app that takes you through Arduino one circuit at a time. Made with Opus 5.5 https://t.co/1AL82geKtQ https://t.co/E2btjzhFtl
- Sep 22, 202649x their median
UCSF Med School is 4.6x more likely to admit Hispanic applicants & 12.6x more likely to admit black applicants, than white applicants w/ the SAME academic & socioeconomic backgrounds. Race has no place in admissions & @CivilRights Division will end these illegal practices! https://t.co/b8CpoKHXPl
- Oct 12, 202637x their median
introducing muse wonder our new frontier model. state-of-the-art at personal agents and professional agents. our largest and most capable model yet—rivals the big bois https://t.co/REYHXbjpf6
- Sep 30, 202637x their median
This is so sad. The guy who took all those stock photos of wooden blocks with letters on them is having trouble making ends meet because of AI. https://t.co/hbRtup4UWI
- Aug 29, 202635x their median
People often ask why today's tech wealth doesn't go towards more public works, like libraries, universities, and museums during the late 1800s. As far as I can tell the answer is that they would literally not be allowed to be built. In 2014, George Lucas, a long-time Bay Area resident who built Lucasfilm in the Bay, wanted to build a museum in the Presidio as a gift to the people of San Francisco, to be personally funded to the tune of ~$700 million. The Presidio Trust rejected it. He then tried to build it in his wife's hometown of Chicago, but local nonprofit Friends of the Parks sued and held the project up for two years, long enough for Lucas to give up on the city. The Lucas Museum of Narrative Art will finally open in Los Angeles next month after more than a decade of planning, eight years of construction, and over $1 billion personally spent by Lucas. Meanwhile, San Francisco has built no major museum projects since the 2016 expansion of SFMOMA, and no new libraries since the North Beach Branch in 2014. Public works, like so many other things, are bottlenecked not by donor will or available funding but by vetocracy
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 311 interactions against 1.1M followers, an engagement rate of 0.027%. Posts are seen about 48K times each, and 0.649% of those impressions turn into an interaction. That is about 4.19% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 18.2 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 16:00 UTC, and Tuesday is the busiest day of the week. Of the 118 posts sampled, 63% carry an image or video, 6% are part of a thread and 38% link out. The account's strongest tracked post pulled 54K interactions, about 174x its own typical post.
- What is Garry Tan's engagement rate on X?
- Garry Tan (@garrytan) has an engagement rate of 0.027%, based on the median interactions across 118 original posts from the last 30 days against 1,143,069 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.027%, Garry Tan sits above the 25th percentile of the 204,491 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 @garrytan have real engagement?
- There is not yet enough sample to rank this account against others of its size.
- When does @garrytan post?
- Most posts go out around 16:00 UTC, and Tuesday is its busiest day, at roughly 18.17 posts per day across the measured window.