frank-primary: shape G v2 — UTIL back to the 0.982 law; the 1.00 force was unbootable

Worker init refuses budget >= device total on BOTH ranks:
  ValueError: Free memory on device cuda:0 (31.29/31.86 GiB ...)
NRestarts=2 crash loop, zero weights loaded. Experts stay at the v1 shape
(graph term 0.07 GiB, KV 3.1665e9 = the 400,700-token ask); only the budget
returns under the law. Arena 17.78 GiB / ~7,912 slots predicted.

scripts/frank-primary.env

@@ -1,15 +1,13 @@
 # frank-primary.env — tcclaviger RDNA4 vLLM production config (dankserver :7770).
 #
-# 2026-10-03 shape G: the arena forced to the flag ceiling. The expert arena is
+# 2026-10-03 shape G (as shipped, after the 1.00 revert): the CUDA-graph plan
+# term dropped from the analytic 0.55 GiB to the measured 0.07 GiB (0 base +
+# 12 MiB/graph — the engine's own post-capture delta is -0.06 GiB), and UTIL at
+# the 0.982 law. Arena 17.78 GiB / ~7,912 slots predicted (F measured 17.52 /
+# 7,653). UTIL stays 0.982 ALWAYS: 1.00 is unbootable on this fork (worker init
+# refuses budget >= device total) and 0.13-GiB-margin boots die under load.
 # `budget - non-expert - KV reserve - graphs - overhead` and the KV reserve is a
-# registry constant, so exactly two terms are reachable: the CUDA-graph estimate
-# (priced at the measured capture — the engine's own post-capture delta is
-# -0.06 GiB, i.e. free, so we charge 12 MiB/graph and nothing else) and the
-# budget, which is `device_total x gpu_memory_utilization` with the field pinned
-# to `le=1`. UTIL 1.00 + graph term 0.07 GiB is therefore the MAXIMUM arena this
-# repo can ask for without editing the image: 18.35 GiB / ~8,016 slots. Frank
-# approved forcing util to 1.00 for this; the measured cost is the free-VRAM
-# margin, which lands at ~1.5 GiB/card (see FRANK_PRIMARY_UTIL).
+# registry constant, so those two terms are the whole flag surface.
 # 2026-10-03 shape F (absorbed): MNBT 2048 + the graph term pinned. Measured on
 # the live deploy: arena 17.52 GiB / 7,653 slots, budget 31.29, graphs 0.32.
 # 2026-10-02 shape E: fp8 KV, MAXLEN 200704 x SEQS 3, pool 3.15e9/rank, and
@@ -175,18 +173,19 @@ FRANK_PRIMARY_MNBT=2048
 FRANK_PRIMARY_GATHER_CHUNKS=32
 FRANK_PRIMARY_GATHER_LANES=64
 # UTIL is an ARENA lever: the fork plans `budget = device_total x util`, and at
-# 31.86 GiB/card every +0.01 is +0.32 GiB of expert cache (~+139 slots). Frank
-# held it at 0.982 and then approved FORCING it to 1.00 to buy the last gig of
-# arena — with the caveat written down, because this endpoint has twice died at
-# the ceiling (the 2x262144 bf16 boot at 0.13 GiB free; the 5x262144 boot at
-# "0 bytes free" on a real 995-token request). At util 1.00 the engine's budget
-# equals the whole card, so anything the registry under-prices shows up as a
-# RUNTIME allocation failure rather than a plan refusal. MEASURED cost of the
-# force: the driver high-water mark moves from 28.28 GiB (shape E) to ~30.4 GiB,
-# i.e. ~1.5 GiB of real free VRAM per card is the safety margin. If a request
-# ever dies with `Tried to allocate ... 0 bytes free`, the rollback is THIS
-# number back to 0.982 (-0.57 GiB of arena), not the window.
-FRANK_PRIMARY_UTIL=1.0
+# 31.86 GiB/card every +0.01 is +0.32 GiB of expert cache (~+139 slots), and
+# 0.982 is Frank's standing law: NEVER 1.00. The 1.00 attempt (2026-10-03,
+# shape G v1) died in worker init BEFORE loading a byte of weights — the fork
+# refuses budget >= device total with
+#   ValueError: Free memory on device cuda:N (31.29/31.86 GiB ...)
+# on BOTH ranks at 09:53 and 09:54, NRestarts=2 — so 1.0 is not even a runtime
+# knife-edge here, it is unbootable. The two historical ceiling deaths (the
+# 2x262144 bf16 boot at 0.13 GiB free; the 5x262144 boot at "0 bytes free" on a
+# real 995-token request) remain the reason the margin exists. Rollback note
+# for the other direction: if a request ever dies with
+# `Tried to allocate ... 0 bytes free`, the first knob back is THIS number
+# down a notch, not the window.
+FRANK_PRIMARY_UTIL=0.982
 # CUDA-graph plan term, priced at the measured capture. expert_plan.py charges
 # estimate_cudagraph_memory() = BASE_MB + PER_GRAPH_MB x n_graphs (defaults
 # 256/52 = 0.55 GiB for our 6-graph plan), and the estimator's own docstring