> MAI-Thinking-1 is a 35B-active, ~1T-total parameters, sparse Mixture of Experts model, a smaller inference footprint than much larger models.
This seemingly nonsensical sentence (of course this will have a smaller inference footprint than larger models) suggests this model's competitors have larger inference footprints and total parameter sizes.
As someone who has spent quite a lot of time on inference, I would a add a small note:
Deployment looks very different for MoE than dense style models so I would say that it is more nuanced than "inference memory reqs remain the same". Memory can be very different for MoE style models.
This seemingly nonsensical sentence (of course this will have a smaller inference footprint than larger models) suggests this model's competitors have larger inference footprints and total parameter sizes.