I can't say WSL2 eats host RAM or vRAM: I moved all my ML training and finetuning stuff (OSS LLMs, TTS, STT, Text2Img) to WSL2 and have only minimal overhead.

I can't say WSL2 eats host RAM or vRAM: I moved all my ML training and finetuning stuff (OSS LLMs, TTS, STT, Text2Img) to WSL2 and have only minimal overhead. A clean Win11 host eats away less than 2GB and I love how you can just use your cuda devices on WSL2, use something like micromamba and cmake your wheels while still being able to switch to Win tools whenever necessary. Idle Cuda devices use around 0.5GB vRAM. Especially the two new experimental features in the last update of WSL2 added a nice QoL improvements: - autoMemoryReclaim – Makes the WSL VM shrink in memory as you use it by reclaiming cached memory - Sparse VHD – Automatically shrinks the WSL virtual hard disk (VHD) as you use it