RDMA Mac Studio cluster - performance questions beyond generation throughput

Jeff Geerling’s RDMA cluster benchmarks showed great generation throughput (31.9 tok/s on 4 nodes for Qwen3 235B), but I have questions about other performance aspects. Anyone with an RDMA cluster setup:

1. Prefill speed - Prompt processing at 32K/64K/128K context. Single node vs clustered. Does aggregate bandwidth help or does RDMA overhead eat it?

2. Time to first token - Latency before output starts. How does it scale with nodes?

3. KV cache - Does cache persist across nodes between turns? Or re-prefill every query?

4. Model loading - Cold-start time for 200B+ models. Single vs distributed.

5. Mixed hardware - Any penalty from mismatched RAM (256GB + 512GB nodes)? What about mixed chip generations (M3 Ultra + future M5 Ultra)?

6. Sustained generation - Does throughput hold for 4K-8K token outputs or degrade?

Currently have M3 Ultra 256GB on order, trying to understand if clustering is a real upgrade path.

Obviously if you just have reference to one data point you don’t need to help me answer all six I’m just casting a wide net