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NVIDIA Robotics engagement report

@NVIDIARobotics - 149K followers on X

Measured over 36 original posts from a 30-day window, last computed on September 26, 2026.

Engagement

Middle of its size range
Per follower
0.128%
of 149K followers
Per impression
2.25%
8.4K views on a typical post
Reach
5.70%
of its followers see a post
Typical post
188
interactions (median)
Saved
0.335%
28 bookmarks on a typical post
Posting rate
2.1/day
active 53% of days
Peak time
19:00 UTC
Wednesday

A typical post picks up 188 interactions against 149K followers, an engagement rate of 0.128%. Measured over 36 original posts, its engagement rate beats 58% 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 8.4K times each, and 2.25% of those impressions turn into an interaction. That is about 5.60% 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 53% of days. Most posts go out around 19:00 UTC, and Wednesday is the busiest day of the week. Of the 36 posts sampled, 92% carry an image or video, 19% are part of a thread and 72% link out. The account's strongest tracked post pulled 2.1K interactions, about 11x its own typical post. Recurring topics include #roscon, #nvidiagtc, #isaacros.

Measured over 36 original posts from a 30-day window, last computed on September 26, 2026. Recurring tags: #roscon, #nvidiagtc, #isaacros.

Compared with accounts its own size

NVIDIA Robotics's engagement rate beats 58% of the tracked X accounts closest to it in follower count (21,185 accounts, accounts of similar size (decile 8 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 65% 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 0.128%, NVIDIA Robotics sits above the 25th percentile of the 212,482 accounts in this comparison. That places it in the below the median band, which runs 0.025% to 0.146%.

p100.004%
p250.025%
p50 (median)0.146%
p750.696%
p902.61%
p9982.9%
Engagement rate as a share of followers, across the 212,482 accounts we have scanned enough to measure. The axis is logarithmic, because the top and bottom of this population are about 22,403 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 percentile0.004%
25th percentile0.025%
50th percentile0.146%
75th percentile0.696%
90th percentile2.61%
99th percentile82.9%

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 Wednesday 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: 19:00 UTC.
0003060912151821
Above the authors' own mediansBelowScale: plus or minus 111%Busiest hour: 19:00 UTC
Show engagement by hour posted, utc as a table
Engagement by hour posted, UTC
Hour (UTC)Vs author medianPosts
00:00 UTC-1%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 UTC0%116K
22:00 UTC-2%100K
23:00 UTC-1%90K
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: Wednesday.
SunMonTueWedThuFriSat
Above the authors' own mediansBelowScale: plus or minus 111%Busiest day: Wednesday
Show engagement by day of week as a table
Engagement by day of week
DayVs author medianPosts
Sunday+5%393K
Monday+1%483K
Tuesday-2%520K
Wednesday-3%472K
Thursday-2%430K
Friday-3%447K
Saturday+2%393K
See what moves engagement across the whole catalogWhat counts as a good engagement rate at this size

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.

This account's posting mix compared with catalog-wide effects
FormatThis accountCatalog effect95% intervalAccounts behind it
Image or video92% of posts+111%+108% to +115%34K
Outbound link72% of posts-41%-42% to -40%32K
Typical length-+15%+14% to +16%32K
  • 92% 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.
  • 72% 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 364 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

  • Sep 23, 202611x their median

    Introducing FLUX 3 Action. An open weights 7B World Action Model that achieves first place on the RoboLab benchmark. It outperforms the previous best open model by 6.1 percentage points while using 56% fewer parameters and running up to 3.95x faster.⁠⁠ FLUX 3 Action removes the usual trade-off between world action model performance and VLA speed: it still predicts video and actions together, but plans more than twice as far ahead and runs faster per second of robot motion than the strongest open VLA. Teams can fine-tune FLUX 3 Action on their own demonstrations to create policies for a particular robot and task. Together with @nvidia, we also integrated FLUX 3 Action natively into @huggingface's LeRobot, with fine-tuning recipes included and edge deployment on NVIDIA Jetson. Beyond robotics, we’re also seeing promising results training task-specific policies for acting in simulated environments like gaming, controlling a vehicle, computer use, and wherever else a model needs to understand a visual environment and then choose what to do next. FLUX 3 Action builds on the same image, video, and audio pretraining as FLUX 3, but uses a smaller architecture designed for practical deployment. In midtraining, we trained the model to predict actions and future frames together. We’re releasing the weights, code, fine-tuning recipe, benchmarks, and reproducible examples so researchers and developers can build on the model with their own robots, environments, and tasks (see below).

    1.8K2347550164K viewsView on X
  • Sep 9, 20264.0x their median

    Building general-purpose humanoid robots requires an end-to-end approach. Join NVIDIA’s Spencer Huang to see how AI agents and NVIDIA Isaac GR00T are accelerating the entire process. Add the session to your calendar πŸ‘‰ https://t.co/QAs0uduPg5 https://t.co/Z0TEE2JTpQ

    60794321537K viewsView on X
  • Sep 21, 20263.9x their median

    Physical AI can only scale as fast as safety scales with it. 🦺 Lessons from more than a decade of autonomous vehicle safety work are helping shape how robots are designed, validated and deployed alongside people. Learn how NVIDIA Halos is helping: https://t.co/dnZQSe5OhH https://t.co/hM8Ejq9ezO

    59481371835K viewsView on X
  • Sep 24, 20263.1x their median

    Physics simulation gives robots a place to learn before they enter the physical world. πŸ€– Developers can model complex interactions, train and evaluate policies, and validate robot behavior in controlled virtual environments before deployment. Explore physics simulation for robotics πŸ”— https://t.co/mQUro2cHUk

    50459181027K viewsView on X
  • Sep 1, 20263.1x their median

    Physical AI is taking on tougher industrial work. 🦾 From development to deployment, @NobleMachines is building general-purpose robots with NVIDIA Isaac GR00T, Jetson, and @ADLINK_IoT edge AI platforms to help bring physical AI into demanding industrial environments. Read the story πŸ“– https://t.co/hWhw9i9xx2

    4678224724K viewsView on X
  • Sep 22, 20262.7x their median

    NVIDIA Isaac ROS 5.0 brings AI agents to robotics development. πŸ€– Announced at #ROSCon, the release adds agentic workflows, Isaac Skills, ROS 2 Lyrical support, GPU-accelerated libraries and NVIDIA Jetson support from Orin Nano to Thor. Open source and available now πŸ“– https://t.co/6idfj67AZE

    4126520926K viewsView on X
  • Sep 2, 20262.4x their median

    Robots are ready to take on complex environments. 🌍 See how AI, simulation, and accelerated computing are redefining what’s possible in robotics at #NVIDIAGTC Berlin. View sessions πŸ‘‰ https://t.co/KuuYG9io52 https://t.co/fPOZUrWjyr

    3825717317K viewsView on X
  • Sep 17, 20262.4x their median

    Agentic AI is moving to the edge. On NVIDIA Jetson AGX Thor, TensorRT Edge-LLM completed MLPerf Edge Agentic 6.4x faster than the llama.cpp reference, reaching 52.33 token/sec for Qwen 3.6 27B model. NVFP4, ~96% of prompt tokens served from hot cache and tree-based MTP made it possible. πŸ‘‰ https://t.co/m3o30Lt8aE

    33153521514K viewsView on X
  • Sep 21, 20262.0x their median

    Humanoid robots can only scale if they can operate safely alongside people. Pras Velagapudi, CTO of @agilityrobotics explains how NVIDIA Halos is helping make that possible. https://t.co/4Ic322WxeZ

    28555162642K viewsView on X
  • Sep 15, 20261.9x their median

    Robot policies can succeed in a demo and still fail as tasks, environments, and conditions change. With open-source Isaac Lab-Arena 0.3, developers can use an experimental agentic workflow to generate environments, evaluate policies at scale, and identify where and why failures occur.

    2913421715K 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.

Recurring topics

#roscon#nvidiagtc#isaacros#nemoclaw#nemotron

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 188 interactions against 149K followers, an engagement rate of 0.128%. Measured over 36 original posts, its engagement rate beats 58% 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 8.4K times each, and 2.25% of those impressions turn into an interaction. That is about 5.60% 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 53% of days. Most posts go out around 19:00 UTC, and Wednesday is the busiest day of the week. Of the 36 posts sampled, 92% carry an image or video, 19% are part of a thread and 72% link out. The account's strongest tracked post pulled 2.1K interactions, about 11x its own typical post. Recurring topics include #roscon, #nvidiagtc, #isaacros.

What is NVIDIA Robotics's engagement rate on X?
NVIDIA Robotics (@NVIDIARobotics) has an engagement rate of 0.128%, based on the median interactions across 36 original posts from the last 30 days against 149,480 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
Is that a good engagement rate?
At 0.128%, NVIDIA Robotics sits above the 25th percentile of the 212,482 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 @NVIDIARobotics have real engagement?
Its engagement rate beats 58% 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 @NVIDIARobotics post?
Most posts go out around 19:00 UTC, and Wednesday is its busiest day, at roughly 2.1 posts per day across the measured window.

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