frank-medium: serve the new R9700s, retire frank-small

The RTX 3090 left Dankserver; two AMD Radeon AI PRO R9700 cards (Navi 48,
gfx1201, 32,624 MiB each) replaced it. FreeToken/CUDA cannot run there at all,
so the `frank-small` service is retired and `frank-medium` takes the endpoint.

New service: charlie12345/ROCmFPX llama.cpp (built for gfx1201 against the
fork's self-contained ROCm 7.14 toolchain, so the host's stale /opt/rocm-6.3.3
never participates) serving kingjones777/Qwen3.8-27B-ROCmFPX-Q8_0-AGENT-GGUF --
a Q8_0_ROCMFPX_AGENT (ftype 115) checkpoint that stock llama.cpp cannot load.
Placeholder config: --split-mode tensor across both cards, 131072 context,
1 slot, f16 KV, MTP draft head on ROCm0.

deploy-remote.sh grows retire_root_llm_small(): the CUDA-era unit is stopped,
disabled and moved to ~/.AGENTTRASH/20260915-frank-small-retire/host-units
before frank-medium starts, because `systemctl disable` has been observed to
delete the unit file itself on this host (2026-08-26 incident).

The retired frank-small repo files (env, unit, serve script) move to
scripts/.AGENTTRASH/, and the planner, dispatcher, service allow-list and the
deployment test seams now name frank-medium.

Follow-up (same session, measured): llama-bench on the host with the correct
multi-device syntax (-dev ROCm0/ROCm1) overturned the tensor choice:

  single R9700   pp4096 1160.9 / tg128 19.42  (d32768: 512 / 18.4)
  layer  2x      pp4096 1991.2 / tg128 18.76  (d32768: 859 / 17.6)
  tensor 2x       pp4096  271.8 / tg128 26.26 (d32768: 229 / 25.1)

This build has no RCCL, so tensor mode falls back to a "meta-backend
butterfly" allreduce and prefill collapses 7x. Served path with MTP:
layer 35.7-46.2 tok/s vs tensor 28.7. SPLIT_MODE=layer, draft pinned to
ROCm1 (the card holding the last target layers). Served prefix cache with
the draft head verified live: turn 2 reprocessed 22 tokens instead of 949.

scripts/serve-frank-medium.sh

@@ -27,11 +27,13 @@
 # what makes the MTP draft land ~0.95 of its guesses.  A stock llama.cpp
 # cannot load this GGUF at all - Q8_0_ROCMFPX exists only in this fork.
 #
-# Parallelism: --split-mode tensor across both cards.  Tensor parallel
-# splits the weights AND the KV cache across the participating devices via
-# the fused "meta device" (unlike -sm layer, which pipelines layers and
-# keeps each layer's KV on its own card).  It requires flash attention and
-# a non-quantized KV cache, and it is disabled from auto-fit (--fit off).
+# Parallelism: --split-mode layer across both cards (operator call
+# 2026-09-15).  Layers are distributed in order and activations hop PCIe at
+# the boundary; measured llama-bench: layer 1991/18.8 tok/s (pp4096/tg128)
+# vs tensor 272/26.3 and single-card 1161/19.4.  Tensor wins decode +40 %
+# but its prefill collapses 7x on this build (no RCCL: "AllReduce init
+# failed; falling back to meta-backend butterfly"), so layer split wins the
+# prefill-heavy agentic workload.
 #
 # Tunables come from frank-medium.env unless FRANK_MEDIUM_ENV_FILE
 # overrides that path.