[tmostak]

You should be able to train/full-fine-tune (i.e. full weight updates, not LoRA) a much larger model with 96GB of VRAM. I generally have been able to do a full fine-tune (which is equivalent to training a model from scratch) of 34B parameter models at full bf16 using 8XA100 servers (640GB of VRAM) if I enable gradient checkpointing, meaning a 96GB VRAM box should be able to handle models of up to 5B parameters. Of course if you use LoRA, you should be able to go much larger than this, depending on your rank.