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
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 212,349 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 | 83.1% |
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.
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 | 92% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 72% 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.β β 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, weβre 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. Weβre 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).
- Sep 9, 20264.0x their median
Building general-purpose humanoid robots requires an end-to-end approach. Join NVIDIAβs Spencer Huang to see how AI agents and NVIDIA Isaac GR00T are accelerating the entire process. Add the session to your calendar π https://t.co/QAs0uduPg5 https://t.co/Z0TEE2JTpQ
- Sep 21, 20263.9x their median
Physical AI can only scale as fast as safety scales with it. π¦Ί 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
- Sep 24, 20263.1x their median
Physics simulation gives robots a place to learn before they enter the physical world. π€ Developers can model complex interactions, train and evaluate policies, and validate robot behavior in controlled virtual environments before deployment. Explore physics simulation for robotics π https://t.co/mQUro2cHUk
- Sep 1, 20263.1x their median
Physical AI is taking on tougher industrial work. π¦Ύ 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 π https://t.co/hWhw9i9xx2
- Sep 22, 20262.7x their median
NVIDIA Isaac ROS 5.0 brings AI agents to robotics development. π€ 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 π https://t.co/6idfj67AZE
- Sep 2, 20262.4x their median
Robots are ready to take on complex environments. π See how AI, simulation, and accelerated computing are redefining whatβs possible in robotics at #NVIDIAGTC Berlin. View sessions π https://t.co/KuuYG9io52 https://t.co/fPOZUrWjyr
- 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. π https://t.co/m3o30Lt8aE
- 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
- 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.
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 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 212,349 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.