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Aether is a UE5 C++ six-degrees-of-freedom (6DOF) movement framework built on Unreal Engine’s Network Prediction Plugin (NPP), according to its developer, Kadmium (Emil). The release post on the Epic Developer Community Forums, dated September 19, 2026, pairs a video with a stress-test table and a set of project figures. Those figures are the developer’s own claims. The post does not include a downloadable raw profiler capture, and no independent reproduction has been published, so treat the numbers as material to verify rather than as established UE5 performance.
What Aether is
Aether is presented as a network-predicted 6DOF movement foundation written in C++ for Unreal Engine 5. The developer says it was motivated by movement requirements in the Sirius project. Its technical manual describes a modular foundation around NPP with four named components: flight dynamics, gravity fields, raycast suspension, and visual smoothing.
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Access is the first thing to settle before you plan around it. The developer’s public architecture showcase describes itself as a read-only architectural showcase, not an open-source plugin, and states that the full implementation is proprietary. Nothing in that showcase lets you download the code and build it yourself.
Setup and availability
The setup details come from the developer, and each one should be checked against the live product page before you commit to it:
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- Engine version: the release post identifies UE 5.7.4 and NPP as the engine setup. The technical manual states a UE5.7+ target.
- Status: the manual lists Aether as early access.
- Distribution: direct distribution from the developer. The manual also lists a roadmap target for the Epic Games Store and FAB, which is not yet a confirmed listing.
- Services: the developer offers technical advisory, code audits, and integration work for custom UE5 movement and NPP projects. That is a commercial offer from the developer, not an independent recommendation.
Compatibility, availability, and license terms are vendor statements that can change. Confirm them on the seller’s live pages before buying or integrating.
The release video
The developer describes the video in these words: “And yes the video is raw,unedited footage of me just messing around with the physics trying to force the network to collapse!” That is the most useful framing in the post. The clip shows deliberate, aggressive physics testing aimed at breaking the network model. It is a stress demonstration, not a product walkthrough, and the post does not provide the capture methodology needed to repeat it.
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The published figures
The developer reports four project values. Each one is a self-reported measurement or configuration value from 2026, and none has an independent benchmark behind it.
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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitches| Figure | Reported value | What the source establishes |
|---|---|---|
| CPU time for vector-math simulation | 16–30 µs | Developer-reported project measurement. Hardware and test conditions for the range are not given in the reviewed material. |
| InputCMD payload | 1.58 KB | Developer-reported project value. Not a capture of live traffic. |
| Dedicated server tick rate | 60 Hz (16.67 ms frame budget) | Developer-reported configuration value. The 16.67 ms figure is the frame budget at 60 Hz. |
| Maximum tested speed | 55,000 cm/s (550 m/s) | Developer-reported maximum in its own tests. The 550 m/s figure is the same value converted to metric units. |
These numbers are not general UE5 performance expectations. Do not use them as a baseline for your own project without measuring it.
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The stress-test table
The developer’s table covers ideal conditions and several simulated network conditions. The simulated conditions include:
- Latency, expressed as round-trip time (RTT)
- Packet loss
- Jitter
- Packet reordering
The developer says the behavior looks visually smooth in several severe scenarios. The most extreme row, labeled “JustNo,” reports micro-stutters, heavy input starvation, frequent resimulations, and noticeable input lag. That row is the most informative part of the table. It shows where the developer says the prediction model strains, not only where it succeeds. The table reports outcomes in terms of visual and reconciliation behavior. It does not provide an independently audited measurement of bandwidth or CPU cost under those conditions.
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Why these are not profiler results
The post labels these figures as key specs and stress-test results. It does not show profiler files or screenshots from Epic’s Network Profiler. Calling them profiler results would imply a capture that readers can inspect, and no such capture is published. Until the author provides one, describe them as self-reported figures.
Checking network behavior with Epic’s Network Profiler
Epic describes Network Profiler as a standalone tool for viewing runtime network traffic. It attributes bandwidth to actors, RPCs, and properties. That makes it the right tool for testing the payload and bandwidth claims yourself.
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- Build the project with stat tracking enabled. Epic’s capture workflow requires this build type.
- Start the capture with the
networkprofiler=truelaunch argument, or use thenetprofileconsole commands. Check Epic’s current documentation for the exact subcommands in your engine version. - Play the scenario you want to measure, under the network conditions you are testing. Use whatever latency, loss, or jitter tool suits your setup.
- Open
<PROJECT_DIRECTORY>/Saved/Profiling/and locate the timestamped.nproffile. - Open the file in the standalone Network Profiler.
- Choose the capture side based on what you are measuring. For replicated actors and properties, use a server-side capture. A client capture shows detailed information only for RPCs sent from that client, so compare client captures for their own view rather than as a substitute for the server view.
If you compare Aether with another movement system
No independent product benchmark for Aether was found in the material reviewed, so any comparison has to be built from your own measurements. Hold these variables constant:
- Unreal Engine version and build type
- Movement model and physics scope
- Prediction and reconciliation behavior
- Latency, packet loss, jitter, and reordering conditions
- CPU cost and server tick budget
- Payload size and bandwidth
- Availability of raw captures, source access, and licensing
Do not infer superiority from the developer’s table alone. The table reports one developer’s test runs, and it does not include a competing system measured under the same conditions.
Where the evidence stands
Aether is a developer-presented NPP-based 6DOF framework with a stress video and a table of self-reported results. The video is raw by the author’s own description. The figures, the simulated network conditions, and the “JustNo” outcomes all come from the developer, and no third party has verified them. If you are evaluating Aether for a project, the practical steps are to confirm the engine version and license on the live pages, then reproduce the stress scenario with Network Profiler on your own build.
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