Given things like the AMD Epyc cores sit at around 40 billion transistors, I would assume a (roughly) even split.
It is also worth noting that the M1 Ultra is an SoC so it'll have more than just CPU/GPU on it, by the looks of things it has some hefty amounts of cache, it'll also have a few IP blocks like a PCIe controller, memory controller, SSD controller (the current "SSDs" look to just be raw storage modules).
All told it likely still has somewhere in the region of 30-40 billion transistors for the GPU. Each GPU core being physically bigger than the 3090 is probably pretty good for some workflows and not so good for others. Generally GPUs benefit from having a huge number of tiny cores for processing in parallel, rather than a small number of massive cores.
Current benchmarks put it at roughly the performance of an RTX 3070, which is good for its power consumption, but not even close to the 3090. As I mentioned in the previous post, it just doesn't have the cores or memory bandwidth needed for the types of workloads that GPUs are built for (although unified memory being physically closer can help here ofc.), certainly not enough to make it a competitor for something like a 3090.
Edit: Oh also, for massively parallel workloads (like what GPUs do), more cores and better bandwidth to feed those cores will be one of the biggest performance drivers. You can get more performance by making those cores bigger (and therefore faster) but you need to crank the transistor count up a _lot_ to match the kinds of throughput that many tiny cores can do.