perf(gen-seat): record prefill measurements — roughly doubled

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.

services/gen-seat-mixed-quant/bench/bench_w4a16_recheck.json

@@ -0,0 +1,29 @@
+{
+  "tag": "w4a16-recheck",
+  "model": "probe",
+  "tok_s_median": 77.51086756145159,
+  "tok_s_mean": 77.55102759761677,
+  "tok_s_min": 69.14223827875307,
+  "tok_s_max": 88.11959921725081,
+  "mtp_accept_median": 0.4493388052895577,
+  "rates": [
+    82.25341481185131,
+    77.12830062541333,
+    78.45783182678721,
+    69.14223827875307,
+    71.73740809898078,
+    77.89343449748986,
+    88.11959921725081,
+    75.67599342440771
+  ],
+  "accs": [
+    0.494824016563147,
+    0.44573643410852715,
+    0.4536489151873767,
+    0.36300174520069806,
+    0.3894927536231884,
+    0.45294117647058824,
+    0.56,
+    0.43238095238095237
+  ]
+}