feat(augaman): second, fixtures-only instance on fv-ml1 GPU 1; CPU vs GPU speed bench (v0.1.2 baseline)

Prime asked for augaman on fv-ml1's utility card, beside vllm-coder. Mirror
augaman-dev's f77164f compose, which parameterises the GPU reservation (GPU_ID,
default 0) and the Homepage card name (CARD_SUFFIX). esh-ml1's resolved config is
unchanged: same config hash, no recreate.

On fv-ml1: augaman:0.1.2 built on-box from the tag, GPU_ID=1, healthy on CUDA
at 1264 MiB, and pytest -m gpu tests/vision passes 3/3 on the Blackwell. It has
its own gallery and no gallery backup, so it is fixtures-only. The host's raw
restic copy of /var/lib/docker/volumes is not a consistent SQLite backup.

docs/pfi/augaman-speed-bench/ holds the harness (augaman-dev's recipe plus a
no-face control frame and a face-count check on every response), the raw rows
and the summary. Server-side, one face:
- esh-ml1 GPU 144 ms
- fv-ml1 GPU 75 ms
- fv-ml1 CPU on 6 cores 152 ms
- esh-ml1 CPU 888 ms
It agrees with augaman-dev's independent esh-ml1 measurement once each
harness's floor is subtracted. This is the before for v0.1.3's detector fix.

persistent-memory.md

@@ -155,6 +155,11 @@ _As of 2026-09-26 ~1620 PT._
   survived the recreate and was then deleted, so the gallery is empty and ready for real
   enrollments. `/recognize` p50 186 ms (1080p, one face). The detector-latency follow-up
   is theirs. Their next release pins the container gid to 10001; nothing is owed by infra-ops.
+- **Second instance on fv-ml1 GPU 1 (Prime, 2026-09-27)**, `GPU_ID=1`, **fixtures-only, no
+  gallery backup**, separate gallery. Its role (bench-only vs future primary) is Prime's call.
+- **Speed bench v0.1.2 "before"** (`docs/pfi/augaman-speed-bench/`), server-side one face:
+  esh GPU 144 ms, fv GPU 75 ms, fv CPU (6 cores) 152 ms, esh CPU 888 ms. **OWED: re-run on
+  v0.1.3** (detector gets one session per canvas, ~2× faster) when augaman-dev tags it.
 
 ### esh-ml1