Modern TEE is actually performant for industry needs these days. Over 400,000x gains of zero knowledge proofs and with nominal differences from most raw inference workloads.
I agree that is performant enough for many applications, I work in the field. But it isn't performant enough to run large scale LLM inference with reasonable latency. Especially not when we compare the throughput numbers for a single-tenant inference inside a TEE vs batched non-private inference.
