Closes the one axis of the original premise left unverified. Measured
cold (cache-busted) on both builds under matching serve configs:
~6.7k-token prompt 3,206 -> 6,334 tok/s prefill (+98%)
~27k-token prompt 2,862 -> 5,085 tok/s prefill (+78%)
TTFT on a ~27k doc 9.43 -> 5.31 s (-44%)
Prefill gains far exceed the +18% decode gain, and that ordering is the
expected one: decode at bs=1 is memory-bandwidth-bound and the weights
are 4-bit under either scheme, so little changes; prefill is
compute-bound, which is where native Blackwell FP4 tensor cores replace
the Marlin dequant-to-BF16 path. The summarizer aliases are the
consumers that feel this.
Adds bench/prefill_bench.py plus the raw JSON. The harness deliberately
uses SystemRandom: a seeded nonce regenerates the previous run's prompts
verbatim, prefix caching then serves them, and the first attempt read
~41k tok/s of cache-hit rather than ~5k of actual prefill.
