llm-router: CPU-offload Coder-14B + Llama-3.1-8B (t_72646029)

- Remove global --n-gpu-layers from router unit ExecStart in preset mode
  (llama.cpp CLI arg outranked per-model INI n-gpu-layers=0; root cause from
  War Machine's run 1). Flag now emitted only in --models-dir mode.
- All 5 preset INI sections carry explicit n-gpu-layers:
  Qwen3.8=99, Phi=99, nomic=99, Coder=0, Llama=0.
- host_vars/astro-orbiter: llm_router_models_max 2 -> 4 so CPU-offloaded
  models count as loaded without LRU-evicting Qwen3.8.
- defaults: llm_router_coder_gpu_layers / llm_router_llama_gpu_layers = 0.
- verify.yml: fix pre-existing .meta attribute crash in router mode.
- New playbook day2_cpu_offload_aux_models.yml.

Deployed + verified on astro-orbiter (gates A-E PASS): concurrent residency
achieved, Qwen3.8 stays GPU-resident. Measured CPU throughput Llama 9.0 /
Coder 4.7 tok/s. VRAM note: llama.cpp 6ea215d allocates ~1.4-1.7GB CUDA-context
per CPU model even at n-gpu-layers=0 -> ~24,004 MiB steady-state, below the
24,576 MiB physical limit. Comments corrected to match the measurement.
Report: friday/inbox/ryan/2026-08-17-llm-cpu-offload-coder-llama-deployed.md

ansible/roles/llm-inference-multimodel/templates/llama-server-router.service.j2

@@ -18,8 +18,8 @@ ExecStart={{ llm_binary_path }} \
     --models-max {{ llm_router_models_max }} \
     --host {{ llm_router_bind_address }} \
     --port {{ llm_router_port }} \
-    --n-gpu-layers {{ llm_router_gpu_layers }} \
 {% if not (llm_router_preset_enabled | default(false)) %}
+    --n-gpu-layers {{ llm_router_gpu_layers }} \
     --ctx-size {{ llm_router_ctx_size }} \
     --flash-attn {{ llm_router_flash_attn }} \
 {% endif %}
@@ -30,7 +30,7 @@ ExecStart={{ llm_binary_path }} \
     --parallel {{ llm_router_parallel }} \
     --metrics
 
-# ROUTER MODE NOTES (2026-08-12, t_0cca74a2 / updated t_9adf0889):
+# ROUTER MODE NOTES (2026-08-12, t_0cca74a2 / updated t_9adf0889 / updated t_72646029):
 # - NO -m/--model flag: this is what enables llama-server router/supervisor mode.
 #   Without -m, llama-server discovers all .gguf files in --models-dir, or uses
 #   the per-model definitions in a --models-preset INI file.
@@ -40,12 +40,16 @@ ExecStart={{ llm_binary_path }} \
 #   The preset INI is at {{ llm_router_preset_path | default('/opt/llama-server-router-preset.ini') }}.
 #   Both the section name and the alias field in the INI work as model IDs.
 #   GH #22364 (extra "default" entry in /v1/models) is expected in preset mode — cosmetic.
+# - --n-gpu-layers is INTENTIONALLY OMITTED from preset mode (t_72646029, 2026-08-17):
+#   In --models-preset mode every model section in the INI sets n-gpu-layers explicitly.
+#   A global CLI --n-gpu-layers has HIGHEST precedence in llama.cpp (CLI > model-section > global-INI)
+#   and would override per-model INI values (e.g. n-gpu-layers=0 for CPU offload).
+#   When preset mode is disabled (--models-dir), --n-gpu-layers is emitted normally.
 # - --models-max {{ llm_router_models_max }} is driven by llm_router_models_max
 #   (default 1 in defaults/main.yml; overridden to 4 in host_vars/astro-orbiter
-#   as of t_33acbb2e after VRAM budget review — see host_vars for OOM risk note).
-#   Default llama-server cap is 4 simultaneous — OOM on 24GB if all 3 current
-#   GGUFs load at once. LRU eviction mitigates in practice but review before adding
-#   models. See host_vars/astro-orbiter/vars.yml for full VRAM breakdown.
+#   as of t_72646029 after CPU-offload enabling — CPU models count against models-max
+#   and hold ~1.4-1.7GB CUDA-context VRAM each (llama.cpp 6ea215d allocates it even at
+#   n-gpu-layers=0); steady-state ~24,004 MiB, below the 24,576 MiB physical limit).
 # - Clients select a model via "model": "<section-name-or-alias>" in their
 #   chat completion request. Hermes sends model: "<id>" on every request already.
 # - Cold model load on first request: ~30-60s for Qwen3.6-35B. First response