NVIDIA AI Infrastructure engagement report
@NVIDIAAIInfra - 86K followers on X
Measured over 30 original posts from a 30-day window, last computed on October 12, 2026.
Engagement
A typical post picks up 107 interactions against 86K followers, an engagement rate of 0.129%. Measured over 30 original posts, its engagement rate beats 56% of 21,185 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 3.9K times each, and 2.75% of those impressions turn into an interaction. That is about 4.54% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.1 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 19:00 UTC, and Thursday is the busiest day of the week. Of the 30 posts sampled, 97% carry an image or video, 17% are part of a thread and 90% link out. The account's strongest tracked post pulled 1.2K interactions, about 11x its own typical post. Recurring topics include #nvidiagtc, #fullyconnected26, #nvidiadgx.
Measured over 30 original posts from a 30-day window, last computed on October 12, 2026. Recurring tags: #nvidiagtc, #fullyconnected26, #nvidiadgx.
Compared with accounts its own size
NVIDIA AI Infrastructure's engagement rate beats 56% of the tracked X accounts closest to it in follower count (21,185 accounts, accounts of similar size (decile 7 of 10)). A percentile is spread evenly by construction, so 50 really is the middle of that group and 90 really is its top tenth.
On engagement per impression rather than per follower it beats 70% of the same group. When those two numbers disagree, the gap is about how far its posts travel rather than how people react to them.
Where this sits in the catalog
At 0.129%, NVIDIA AI Infrastructure sits above the 25th percentile of the 212,567 accounts in this comparison. That places it in the below the median band, which runs 0.025% to 0.146%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.025% |
| 50th percentile | 0.146% |
| 75th percentile | 0.696% |
| 90th percentile | 2.61% |
| 99th percentile | 82.7% |
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 19:00 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% | 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 | 97% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 90% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | +15% | +14% to +16% | 32K |
- 97% 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.
- 90% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts, so a large share of this account's output sits in the weakest bucket we measure.
- Its average post runs 392 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 12, 202611x their median
Open standards are the foundation for AI factories that can scale from megawatts to gigawatts. At #OCPSummit26, we contributed the NVIDIA Vera Rubin NVL72 rack and compute tray designs to @OpenComputePrj through the open 3rd generation NVIDIA MGX architecture. We also announced advances across open source software, AI networking, pluggable optics, facility design standards and more, giving the industry a common foundation for next-generation AI factories. Learn more: https://t.co/gD6McBTN4c
- Sep 2, 202611x their median
4000 GB200s just arrived in Texas for the Horizon TACC cluster. I'm informed this is the largest academic supercomputer. Very excited to start training some open models with this bad-ass machine. (photo courtesy of Adam Klivans, director of NSF IFML) https://t.co/qCcueV5P3q
- Sep 4, 20269.8x their median
We are excited to receive our first production NVIDIA Vera Rubin NVL72 racks! A huge thank you to our partners @nvidia and @DellTech for this historic moment. Our engineering and data center teams are bringing up the units...stay tuned for more! https://t.co/yBorCa3EGR
- Sep 30, 20267.6x their median
Cognition is the first customer running @NVIDIA Vera Rubin, powered by @CoreWeave! Hopper in 2022. Blackwell in 2024. Now Vera Rubin: On SWE-2 inference, the new chips deliver about 4.8x more token throughput than GB200 at the same decode speed. More compute, better agents! https://t.co/2fRCp0yKGN
- Aug 28, 20267.6x their median
Quantum systems only become useful when integrated with AI supercomputing, and we're building the platform to make that happen. Across the world, supercomputing centers are connecting quantum processors with NVIDIA GPUs. ✔️ NVIDIA CUDA-Q lets developers write once and deploy across all major physical quantum processors. ✔️ NVIDIA Ising, our open-source model family, brings AI to quantum by cutting logical error rates by over 300x and compressing qubit calibration timelines from days to hours. ✔️ NVIDIA NVQLink connects quantum processors to GPUs for real-time error correction with microsecond QPU-GPU latency. Learn more about how we're advancing quantum computing ➡️ https://t.co/UDa7mdlEgC
- Sep 6, 20265.6x their median
We're heading to #SEMICONWest 2026! Join us to see how we're enabling the semiconductor ecosystem to accelerate innovation across chip design, manufacturing, and production. Learn how accelerated computing and AI technologies are powering smart factories and scaling semiconductor workloads. @SEMIconex 📆 October 13-15 📍San Francisco, CA 🔗 Learn more and register: https://t.co/lipyyPGO1k
- Sep 24, 20265.0x their median
Ten years ago at NVIDIA GTC 2016, our CEO @JensenHuang introduced DGX-1, our first AI supercomputer. Since then, NVIDIA DGX has transformed from a single system into a blueprint for AI factories. What hasn’t changed is the reason why we build DGX: to test the systems and work through the details of interconnects, cooling, and software so our partners and customers have a proven foundation to build on. Charlie Boyle, our VP of DGX Systems, looks back at how DGX got its start, what’s changed, and what comes next. Thanks to everyone who’s been on this journey with us. #DecadeOfDGX Watch the full video: https://t.co/bvgdjJupU0
- Sep 30, 20264.5x their median
NVIDIA Vera Rubin NVL72 is live on @CoreWeave, and the results speak for themselves. @Cognition tested it on real-world software engineering workloads and saw 4.8x higher token throughput vs. GB200 NVL72. From Volta to Vera Rubin, CoreWeave delivers every NVIDIA platform to production that stays productive, durable and fungible across generations. Read the news from #FullyConnected26 ➡️ https://t.co/M6Ik3Pz0L3
- Aug 24, 20264.4x their median
📣 @ArtificialAnlys' 100K context inference benchmark results are in. NVIDIA Groq 3 LPX generated 3,431 output tokens/second on the Gemma 4 31B model at 100K context, nearly 4x the next fastest public endpoint on this benchmark. Paired with NVIDIA Vera Rubin NVL72, Groq 3 LPX extends the Vera Rubin platform's ability to serve multiagent systems powered by 2T+ parameter models with high interactivity and long context. See the results: https://t.co/EUyD6sPhNv
- Aug 27, 20264.3x their median
Building the next generation of semi-custom AI factories requires more than just compute. XPUs also need fast memory, high-bandwidth connectivity, and rack-scale infrastructure. NVIDIA NVLink Fusion is expanding with NVHBM, a next-generation high-bandwidth memory technology that extends innovation to another critical layer of the AI stack. Through the proven NVLink fabric, NVLink Fusion integrates custom XPUs into our AI infrastructure platform, enabling hyperscalers and AI-native companies to combine custom silicon with NVIDIA scale-up networking, high-bandwidth memory and rack-scale architecture. Learn more: https://t.co/HofBAsZs96
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.
Recurring topics
The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.
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Reading these numbers
A typical post picks up 107 interactions against 86K followers, an engagement rate of 0.129%. Measured over 30 original posts, its engagement rate beats 56% of 21,185 tracked accounts of a similar size, which puts it in the middle of its size range rather than at either end. Posts are seen about 3.9K times each, and 2.75% of those impressions turn into an interaction. That is about 4.54% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.1 posts a day over the last 30 days, with activity on roughly 50% of days. Most posts go out around 19:00 UTC, and Thursday is the busiest day of the week. Of the 30 posts sampled, 97% carry an image or video, 17% are part of a thread and 90% link out. The account's strongest tracked post pulled 1.2K interactions, about 11x its own typical post. Recurring topics include #nvidiagtc, #fullyconnected26, #nvidiadgx.
- What is NVIDIA AI Infrastructure's engagement rate on X?
- NVIDIA AI Infrastructure (@NVIDIAAIInfra) has an engagement rate of 0.129%, based on the median interactions across 30 original posts from the last 30 days against 85,683 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.129%, NVIDIA AI Infrastructure sits above the 25th percentile of the 212,567 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 @NVIDIAAIInfra have real engagement?
- Its engagement rate beats 56% of the tracked X accounts closest to it in follower count (21,185 accounts), which puts it in the middle of its size range group. Ranking inside a size band matters because engagement rate falls as accounts grow, so a raw rate would mostly re-measure the follower count. It is a starting point for a look at follower quality, not a verdict on it.
- When does @NVIDIAAIInfra post?
- Most posts go out around 19:00 UTC, and Thursday is its busiest day, at roughly 2.1 posts per day across the measured window.