We're talking 16 GPUs for ~6 hrs for inference, and 48 hrs for pre-training. This is not an exorbitant amount of compute.
A GPU costs $1-2/hr on the cloud market. So, ~$100-200 for inference, and ~$800-1600 for pre-training, which amortizes across chips. Cloud prices are an upper bound -- most CS labs will have way more than this available on premises.
In an industry context, these costs are completely dwarfed by the rest of the chip design process. (For context, the licensing costs alone for most commercial EDA software are in the millions of dollars.)
A GPU costs $1-2/hr on the cloud market. So, ~$100-200 for inference, and ~$800-1600 for pre-training, which amortizes across chips. Cloud prices are an upper bound -- most CS labs will have way more than this available on premises.
In an industry context, these costs are completely dwarfed by the rest of the chip design process. (For context, the licensing costs alone for most commercial EDA software are in the millions of dollars.)