AI at Meta engagement report
@AIatMeta - 841K followers on X
Measured over 6 original posts from a 30-day window, last computed on August 30, 2026.
Engagement
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 1.2K interactions against 841K followers, an engagement rate of 0.138%. Posts are seen about 242K times each, and 0.478% of those impressions turn into an interaction. That is about 28.8% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.93 post a day over the last 30 days, though only 20% of days saw any activity at all. Most posts go out around 10:00 UTC, and Thursday is the busiest day of the week. Of the 6 posts sampled, 100% carry an image or video and 17% link out. The account's strongest tracked post pulled 18K interactions, about 16x 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 30, 2026.
Where this sits in the catalog
At 0.138%, AI at Meta sits above the 50th percentile of the 36,261 accounts in this comparison. That places it in the above the median band, which runs 0.08% to 0.431%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.002% |
| 25th percentile | 0.012% |
| 50th percentile | 0.08% |
| 75th percentile | 0.431% |
| 90th percentile | 2.10% |
| 99th percentile | 160.7% |
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 10:00 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.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 50K |
| 01:00 UTC | -2% | 51K |
| 02:00 UTC | -3% | 50K |
| 03:00 UTC | -4% | 53K |
| 04:00 UTC | -6% | 43K |
| 05:00 UTC | -4% | 42K |
| 06:00 UTC | -4% | 48K |
| 07:00 UTC | -5% | 51K |
| 08:00 UTC | -4% | 60K |
| 09:00 UTC | -3% | 69K |
| 10:00 UTC | -2% | 71K |
| 11:00 UTC | -3% | 78K |
| 12:00 UTC | -2% | 86K |
| 13:00 UTC | -2% | 93K |
| 14:00 UTC | -3% | 96K |
| 15:00 UTC | -2% | 100K |
| 16:00 UTC | -3% | 97K |
| 17:00 UTC | -2% | 90K |
| 18:00 UTC | -1% | 84K |
| 19:00 UTC | -2% | 79K |
| 20:00 UTC | -1% | 74K |
| 21:00 UTC | -1% | 66K |
| 22:00 UTC | -2% | 57K |
| 23:00 UTC | -2% | 51K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +4% | 229K |
| Monday | 0% | 284K |
| Tuesday | -2% | 273K |
| Wednesday | -1% | 250K |
| Thursday | -2% | 243K |
| Friday | -3% | 251K |
| Saturday | +3% | 226K |
Best tweets
- Jun 29, 202616x their median
We’re sharing the next major milestone in our non-invasive brain-to-text decoder research: Brain2Qwerty v2. Building on v1, which was published today in @Nature, Brain2Qwerty v2 is the highest-performing end-to-end pipeline capable of real-time sentence decoding from raw brain signals. It advances beyond character-level performance to decoding words and semantics, enabling accuracy for overall communication. We believe this research has the potential to make a real difference for the millions of people who suffer from brain lesions or disorders that prevent them from communicating. 🧵👇
- Aug 10, 20268.8x their median
Introducing Muse Glimmer, an open-weight 30B-parameter model optimized for local, always-on agent workflows. Muse Glimmer delivers strong performance on key agentic use cases and benchmarks compared with leading models in its size category, and is designed to run entirely on consumer hardware like a Mac or PCs with performant GPUs. In keeping with our long tradition of sharing fundamental AI research, we’re releasing model weights under a permissive Apache 2.0 license. 🧵👇
- Jul 9, 20265.4x their median
We’re excited to introduce Muse Spark 1.1, a significant upgrade from the first Muse Spark model we released earlier this year. Along with this release, we are launching a public preview of the new Meta Model API where developers can access Muse Spark 1.1. The model is also available now in "Thinking" mode in the Meta AI app and on https://t.co/wHkMPH82ZH. Learn more: https://t.co/zGcA3XaWpN
- Aug 5, 20263.8x their median
Introducing Muse Code (beta), a terminal coding agent built for long-horizon software engineering, powered by our new Muse Spark 1.2 model. Muse Code plans, implements, and validates complex, multi-file changes across large repositories with persistent sub-agents that solve difficult problems faster, more accurately, and with less intervention. 🧵👇
- Jul 7, 20262.8x their median
Introducing Muse Image and Muse Video, the first media generation models developed by Meta Superintelligence Labs. Muse Image is our most advanced image generation model yet. It follows instructions faithfully, edits with precision, composes from multiple references, and draws on Instagram for social context. It also brings agentic tool use capabilities to image generation and integrates with Muse Spark. You can try Muse Image in the Meta AI app and web, as well as in Instagram Stories and WhatsApp – starting in limited countries with more locations on the way. Today we’re also previewing Muse Video, which is built upon the same pretraining base as Muse Image to deliver exceptional visual fidelity with native audio support. Learn more about both models: https://t.co/QtKDPDZP5v
- Apr 10, 20261.7x their median
the muse spark API will be coming soon! we have been thrilled with the amount of excitement amongst developers who want to try muse spark inside their agentic harnesses stay tuned!
- Aug 6, 2026
To understand whether we're making genuine progress on reasoning, we entered our AI models in five STEM Olympiad competitions. The results: 🏅 Asian Physics Olympiad (APhO): Perfect score, theory exam 🏅 International Physics Olympiad (IPhO): Perfect score, theory exam 🥇 International Mathematical Olympiad (IMO): Gold medal 🥇 International Chemistry Olympiad (IChO): Gold-medal-level performance 🥇 Romanian Masters of Mathematics (RMM): Gold-medal-level performance The types of problems in the Olympiad competitions are exceptionally hard, demanding deep chains of reasoning, creative insight, and flawless argumentation. To test pure reasoning capability, we disallowed all tool use, meaning no search, no coding, and no calculator. We have deep admiration for the contestants and committees behind these competitions, and are grateful for their support in enabling our participation.
- Apr 24, 2026
Today we’re announcing an agreement with Amazon Web Services to bring tens of millions of AWS Graviton cores to our compute portfolio. This partnership marks an expansion of our diversified AI infrastructure and will help scale systems behind Meta AI and agentic experiences that serve billions of people. Learn more: https://t.co/cmeATOB7Jc
- Apr 8, 2026
Ok this is actually pretty impressive and I truly didn't see any model doing this before or being able to do it to this extent. When I asked Muse Spark from Meta to convert this image into code, it cut out the assets from the screens so it could use them correctly! https://t.co/eyTlSHk2Bh
- Jul 9, 2026
We gave a few leaders early access to Muse Spark 1.1, here's what they had to say: https://t.co/66Evscf2TM
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.
Buy or sell X accounts - escrow-protected
PlayerSells is an escrow marketplace for X accounts. Every deal is protected, with no middleman risk.
Reading these numbers
A typical post picks up 1.2K interactions against 841K followers, an engagement rate of 0.138%. Posts are seen about 242K times each, and 0.478% of those impressions turn into an interaction. That is about 28.8% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 0.93 post a day over the last 30 days, though only 20% of days saw any activity at all. Most posts go out around 10:00 UTC, and Thursday is the busiest day of the week. Of the 6 posts sampled, 100% carry an image or video and 17% link out. The account's strongest tracked post pulled 18K interactions, about 16x 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 AI at Meta's engagement rate on X?
- AI at Meta (@AIatMeta) has an engagement rate of 0.138%, based on the median interactions across 6 original posts from the last 30 days against 841,090 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.138%, AI at Meta sits above the 50th percentile of the 36,261 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 @AIatMeta have real engagement?
- There is not yet enough sample to rank this account against others of its size.
- When does @AIatMeta post?
- Most posts go out around 10:00 UTC, and Thursday is its busiest day, at roughly 0.93 posts per day across the measured window.