How to Play 'Subnautica 2' in VR, Although You May Want to Wait
Subnautica 2 launched into early access yesterday, already having sold over two million copies in the first 12 hours. While it doesn’t include native VR support, that hasn’t stopped the most intrepid of us, who are.
Condensed by AI-Portable from Editorial queue.
Subnautica 2 launched into early access yesterday, already having sold over two million copies in the first 12 hours. While it doesn’t include native VR support, that hasn’t stopped the most intrepid of us, who are already swimming around the depths in VR.
It’s no surprise that many Subnautica 2 owners have quite literally already popped their heads into the non-VR game. Like many games built in Unreal Engine, Subnautica 2 can be played in VR already thanks to PrayDog’s UEVR mod suite .
One such user was YouTuber ‘LunchAndVR’, who showed off some of the first footage of playing the game in immersive VR. Here’s the quick, spoiler-free video:
LunchAndVR notes that for now, they’re only able to play in VR with 3DOF and head aiming, which is admittedly less than ideal when it comes to user comfort and immersion, since most VR gamers expect 6DOF and immersive hand controls.
Some pitfalls to avoid include disabling autosave in the game’s accessibility settings, LunchAndVR says, otherwise the game crashes repeatedly. To do that, simply go to Subnautica 2 settings > Debug Settings > Disable Auto Save. At least for now, that means you’ll need to disable VR mode, save whilst in flatscreen, and then re-enable VR.
The portable AI angle here is not just that Editorial queue published a new item. It is that this material changes how readers should think about portable ai systems in practical terms: what shifts on-device, what still depends on platform or cloud layers, and what kind of user workflow becomes more or less realistic as a result.
From an editorial standpoint, the most useful question is whether this review candidate produces a real behavioral or product constraint change. If the answer is yes, it belongs in AI-Portable because it tells us something about interface friction, local capability, deployment readiness, or the specific work conditions where portable AI may actually land first.
This matters because it touches portable ai through a review candidate signal, which affects real device-side constraints, deployment timing, or product readiness.
Even when the source is directionally useful, the editorial job is to separate confirmed facts from launch framing. Availability, sustained usage evidence, implementation complexity, privacy implications, and integration cost often determine whether a portable AI signal is operationally meaningful or just momentarily interesting.