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Google DeepMind engagement report

@GoogleDeepMind - 1.5M followers on X

Measured over 6 original posts from a 30-day window, last computed on August 31, 2026.

Engagement

Per follower
0.06%
of 1.5M followers
Per impression
0.838%
108K views on a typical post
Reach
7.15%
of its followers see a post
Typical post
906
interactions (median)
Saved
0.15%
162 bookmarks on a typical post
Posting rate
0.63/day
active 33% of days
Peak time
14:00 UTC
Thursday

Early reading. We have captured 6 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 906 interactions against 1.5M followers, an engagement rate of 0.06%. Posts are seen about 108K times each, and 0.838% of those impressions turn into an interaction. That is about 7.15% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.63 post a day over the last 30 days, though only 33% of days saw any activity at all. Most posts go out around 14:00 UTC, and Thursday is the busiest day of the week. Of the 6 posts sampled, 83% carry an image or video, 33% are part of a thread and 67% link out. The account's strongest tracked post pulled 4.4K interactions, about 4.8x its own typical post. Only 6 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 6 original posts from a 30-day window, last computed on August 31, 2026.

Where this sits in the catalog

At 0.06%, Google DeepMind sits above the 25th percentile of the 36,134 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%
p750.431%
p902.11%
p99161.6%
Engagement rate as a share of followers, across the 36,134 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 107,713 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 percentile0.431%
90th percentile2.11%
99th percentile161.6%

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 14:00 UTC, and Thursday 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: 14:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 6%Busiest hour: 14:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%50K
01:00 UTC-2%51K
02:00 UTC-4%49K
03:00 UTC-4%53K
04:00 UTC-6%42K
05:00 UTC-4%41K
06:00 UTC-4%47K
07:00 UTC-5%51K
08:00 UTC-4%60K
09:00 UTC-3%68K
10:00 UTC-2%71K
11:00 UTC-3%77K
12:00 UTC-2%85K
13:00 UTC-2%93K
14:00 UTC-3%96K
15:00 UTC-2%99K
16:00 UTC-3%96K
17:00 UTC-2%89K
18:00 UTC-2%83K
19:00 UTC-2%79K
20:00 UTC-1%73K
21:00 UTC-1%65K
22:00 UTC-1%57K
23:00 UTC-2%51K
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: Thursday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 5%Busiest day: Thursday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+4%228K
Monday0%281K
Tuesday-2%270K
Wednesday-1%249K
Thursday-2%242K
Friday-3%250K
Saturday+3%225K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

Best tweets

  • Aug 18, 20264.8x their median

    Matrix multiplication is the basic computational operation that powers modern computing (including AI). Yet, the theoretical fastest speed at which computers can multiply matrices (omega ω) is still unknown and has been a longstanding challenge for complexity theory and computer science. Today, we announce a new record for omega (ω<2.371177). This is the result of a great team effort between @GoogleDeepMind, our academic collaborators, and our Gemini-powered coding agent AlphaEvolve! 🧮 https://t.co/5c7E8W1F1d

    3.8K4089260467K viewsView on X
  • Jun 11, 20264.3x their median

    We’re teaming up @Palmeiras, the first football club to meaningfully build upon TacticAI: our AI system that can help simulate field scenarios and predict open play dynamics up to 8 seconds in advance. ⚽

    3.3K3871161321.0M viewsView on X
  • Jul 16, 20263.4x their median

    This is great news. As you age, sugar binding to your proteins creates stiff, sticky chemical scars that affect skin, arteries, eyes and more. It was considered irreversible and now may be reversible, restoring to a healthy state. Researches did this by using AlphaFold to search 45,000 oxidases, then screened more than 500 million engineered variants through directed evolution. The work is still ex vivo in a lab setting. Delivering a large bacterial enzyme safely into living tissues, with sufficient penetration and bioavailability, remains a major challenge.

    2.7K19314430281K viewsView on X
  • Jul 29, 20262.9x their median

    https://t.co/51C2lyfTCM

    2.3K2037566388K viewsView on X
  • Jul 15, 20261.9x their median

    From proposing hypotheses to designing experiments, AI agents are starting to reshape scientific discovery. But the hardest part is testing these ideas in the real world. Our essay explores the growing validation bottleneck and outlines four priorities for policymakers and funders. → https://t.co/biz1QlHNtm

    1.5K150932710M viewsView on X
  • Jul 17, 20261.8x their median

    We're announcing a major update to Weather Lab, our interactive website for sharing Google’s AI weather models from @GoogleDeepMind and @GoogleResearch: https://t.co/7vCH7Qw2Fo https://t.co/EOnX9Ubjb5

    1.4K1994617177K viewsView on X
  • Jul 29, 20261.7x their median

    Meet Lyria 3.5, the newest music model from @GoogleDeepMind, now powering Flow Music: 🎤 Vocals: More expressive, dynamic singing 🎸 Musicality: Richer arrangements with tracks that flow naturally. 🎛️ Controls: Better at following creative directions - now featuring BPM control and exportable stems for full-length songs! Try it now at https://t.co/hqlIaESXXJ! 🧵

    1.2K1667672155K viewsView on X
  • Jul 30, 20261.6x their median

    This is how Gemini Robotics 2 helps @Apptronik’s Apollo 2 use whole body intelligence to pack for a sports game ↓ https://t.co/rPYsclzJHR

    1.2K1768433143K viewsView on X
  • Aug 21, 20261.6x their median

    Games have been an important testbed for our AI research for over 15 years. 🎮 From mastering Atari to reaching Grandmaster in StarCraft II, they have driven some of our biggest AI breakthroughs. Our work with SIMA taught agents how to understand 3D worlds, but learning to navigate real human dynamics takes a living, persistent universe. Through our research partnership with @FenrisCreations, we’re exploring how to tackle open challenges in AI: 🔵 Continual learning to acquire new skills without forgetting past knowledge. 🔵 Deep memory systems that store and retrieve information far beyond today’s context windows. 🔵 Long-horizon planning over weeks, months, or years. 🔵 Multi-agent dynamics spanning cooperation, negotiation, economics, and emergent behaviors. Our long-term goal is to use AI to discover entirely new gameplay experiences in partnership with game developers – making games more accessible and personalized – while applying what we've learned to problems in the real world and scientific discovery. Find out more → https://t.co/fAbYdukA5A

    1.1K14811742152K viewsView on X
  • Jul 23, 20261.6x their median

    Gemini 3.5 Flash Cyber is our specialized, lightweight model built to help security teams spot and patch vulnerabilities before they can be exploited. 🧵 https://t.co/XpiKcvwjeI

    1.1K12210454134K 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 906 interactions against 1.5M followers, an engagement rate of 0.06%. Posts are seen about 108K times each, and 0.838% of those impressions turn into an interaction. That is about 7.15% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.63 post a day over the last 30 days, though only 33% of days saw any activity at all. Most posts go out around 14:00 UTC, and Thursday is the busiest day of the week. Of the 6 posts sampled, 83% carry an image or video, 33% are part of a thread and 67% link out. The account's strongest tracked post pulled 4.4K interactions, about 4.8x its own typical post. Only 6 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 Google DeepMind's engagement rate on X?
Google DeepMind (@GoogleDeepMind) has an engagement rate of 0.06%, based on the median interactions across 6 original posts from the last 30 days against 1,512,403 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.06%, Google DeepMind sits above the 25th percentile of the 36,134 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 @GoogleDeepMind have real engagement?
There is not yet enough sample to rank this account against others of its size.
When does @GoogleDeepMind post?
Most posts go out around 14:00 UTC, and Thursday is its busiest day, at roughly 0.63 posts per day across the measured window.

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