Earlier quoted context omitted.
It's a very plausible rumor, but it is misleading in this context, because the rumor also states that it's a mixture of experts model with 8 experts, suggesting that most (perhaps as many as 7/8) of those weights are unused by any particular inference pass. That might suggest that GPT-4 should be thought of as something like a 250B model. But there's also some selection for the remaining 1/8 of weights that are used…
What is the reason for settling on 7/8 experts for mixture of experts? Has there been any serious evaluation of what would be a good MoE split?
Everyone seems to put each expert on a different GPU in training and inference, so that's how you get to 8 experts, or 7 if you want to put the router on its own GPU too.
You could also do multiples of 8. But from my limited understanding it seems like more experts don't perform better. The main advantage of MoE is the ability to split the model into parts that don't talk to each other, and run these parts in different GPUs or different machines.