Unless I’m mistaken, that OOM message relates to your system RAM rather than VRAM. If this is a cluster submission, your job may be being terminated by the scheduler when it consumes more than what was requested.
You may want to review the exact setup of your cluster submission script. The default {{ ram_gb }} value for the class_2d jobtype is often limiting. You may wish to either a) create a bespoke lane with, e.g. {{ (ram_gb*2)|int }} (or similar) for such situations, or b) edit the job-specific memory requirement as suggested here.
Cheers,
Yang