Tensor split performance on low-bandwidth (TB3) eGPUs, and a question

Hey everyone!

I've got a pair of Morefine G1 4090M 16gb eGPUs connected at 40Gbps via TB3 (daisy-chained). I normally run them in layer split mode as it doesn't seem to need much bandwidth; I'm seeing around 1300t/s PP and 26t/s TG (35-40 with MTP), qwen3.6-27B @ Q4. Which is great.

Started playing around with tensor mode (using different USB topologies) and I noticed that it actually does seem to need less bandwidth and saturate both cards during TG, but hit a wall during PP.

With MPT (draft-n-max 3) I'm seeing 50-60t/s in tensor split mode and both cards are totally saturated (pulling 140W each), about 200MB/s bandwidth in each direction (so 800MB/s total for the two cards).

But PP saturates the links and performance is poor, as expected - around 500-600t/s with an empty context.

It just got me wondering, though. Is it in theory possible (mathematically/programmatically) to "hybrid" split a model in such a way it could run prefill on one card at a time (reducing bandwidth requirements) and decode across both? I mean, I guess if you had enough vram you could load the model twice (once per split mode), but would there in theory be a way without significantly increasing memory requirements?

If those of us with very low bandwidth topologies could get tensor split performance on TG and layer split performance on PP that'd be pretty sweet. :)