Wait, what do you mean? 700k A100e hours are equal to 200 hours of a GB300 NVL72 rack? One GB300 NVL72, 72-GPU rack has equal processing power to 3500 A100e GPUs?

maybe? ai says about *8.3 days* of continuous runtime on a single GB300 NVL72 rack

about a sprint's level of effort.

> based on FP4 FLOPs (yes it's disadvantageous to A100, that's the point)

The A100 doesn't have hardware FP4, and you'd be running a quantized model with some accuracy loss but unless this was natively trained on FP4*

* to add another layer, they own the model and could apply tons of post-training techniques to reduce that accuracy loss and probably already do